The rapid growth of the Internet of Things (IoT), cloud computing, Fog computing, mobile edge computing
and wireless grids has resulted in the widespread deployment of relatively immature technology. These
technologies, which will primarily use 5G wireless communication networks, are becoming popular
because they can be deployed quickly with little infrastructure and lends themselves to environments
utilizing numerous internet connected devices (ICD). There are, however, many significant challenges
faced by security designers, engineers and implementers of these networks in ensuring that the level of
security afforded is appropriate. Because of the threat of exploitation, these networks have to be protected
by a robust security architecture due to these technologies being plagued with security problems. The
authentication of smart ICDs to IoT networks is a critical mechanism for achieving security on these new
information system platforms. This article identifies an authentication process required for these ICDs,
which will need to prove their identity to authenticate to an IoT fog-mobile edge computing (FMEC) cloud
network through a wireless grid authentication process. The purpose of this article is to begin to
hypothesize a generic authentication methodology for these FMEC clouds uses in an IoT architecture. The
proposed methodology, called wg-IoT, must include the integration of Fog computing, wireless grids and
mobile edge computing clouds to create this new IoT architecture. An authentication process developed
from the resource sharing protocol (RSP) from a wireless grid is first developed and proposed for the
authentication of ICDs. The wireless grid core components must be embedded in IoT devices or sensors
depending on their capability to handle five primary functions: management of identification [ID] and
presence, permissions management, data transferability, application-programming interface [API] and
security.
SECURITY AND PRIVACY AWARE PROGRAMMING MODEL FOR IOT APPLICATIONS IN CLOUD EN...ijccsa
This document summarizes a research paper on privacy-preserving techniques for IoT data in cloud environments. It introduces two differential privacy algorithms: 1) Generic differential privacy (GenDP) which provides generalized privacy protection for homogeneous and heterogeneous IoT metadata through data portioning. 2) Cluster-based differential privacy which groups similar data into clusters before defining classifiers to validate privacy. The paper evaluates these techniques and finds the cluster-based approach offers better security than customized interactive algorithms while maintaining data utility. Overall, the study presents new differential privacy methods for anonymizing IoT metadata stored in the cloud.
A new algorithm to enhance security against cyber threats for internet of thi...IJECEIAES
One major problem is detecting the unsuitability of traffic caused by a distributed denial of services (DDoS) attack produced by third party nodes, such as smart phones and other handheld Wi-Fi devices. During the transmission between the devices, there are rising in the number of cyber attacks on systems by using negligible packets, which lead to suspension of the services between source and destination, and can find the vulnerabilities on the network. These vulnerable issues have led to a reduction in the reliability of networks and a reduction in consumer confidence. In this paper, we will introduce a new algorithm called rout attack with detection algorithm (RAWD) to reduce the affect of any attack by checking the packet injection, and to avoid number of cyber attacks being received by the destination and transferred through a determined path or alternative path based on the problem. The proposed algorithm will forward the real time traffic to the required destination from a new alternative backup path which is computed by it before the attacked occurred. The results have showed an improvement when the attack occurred and the alternative path has used to make sure the continuity of receiving the data to the main destination without any affection.
Internet of things: review, architecture and applicationsCSITiaesprime
Devices linked to the internet of things (IoT) may communicate with one another in several settings. Furthermore, rather of relying on an existing centralized system, users may develop their own network by using wireless capabilities. This kind of network is known as a wireless mobile ad hoc network. The mobile ad-hoc network (MANET) enables IoT devices to connect with one another in an unstructured networked environment. IoT devices may connect, establish linkages, and share data on a continuous basis. In this system, the cloud's purpose is to store and analyze data acquired from IoT devices. One of the most significant challenges in cloud computing has been identified as information security, and its resolution will result in an even bigger increase in cloud computing usage and popularity in the future. Finally, the goal of this project is to create a framework for facilitating communication between IoT devices in a Cloud and MANET context. Our major contribution is a ground-breaking research initiative that combines cloud computing with the MANET and connects the internet of things. This research might be used to the IoT in the future.
SECURITY& PRIVACY THREATS, ATTACKS AND COUNTERMEASURES IN INTERNET OF THINGSIJNSA Journal
The idea to connect everything to anything and at any point of time is what vaguely defines the concept of the Internet of Things (IoT). The IoT is not only about providing connectivity but also facilitating interaction among these connected things. Though the term IoT was introduced in 1999 but has drawn significant attention during the past few years, the pace at which new devices are being integrated into the system will profoundly impact the world in a good way but also poses some severe queries about security and privacy. IoT in its current form is susceptible to a multitudinous set of attacks. One of the most significant concerns of IoT is to provide security assurance for the data exchange because data is vulnerable to some attacks by the attackers at each layer of IoT. The IoT has a layered structure where each layer provides a service. The security needs vary from layer to layer as each layer serves a different purpose. This paper aims to analyze the various security and privacy threats related to IoT. Some attacks have been discussed along with some existing and proposed countermeasures.
SECURITY& PRIVACY THREATS, ATTACKS AND COUNTERMEASURES IN INTERNET OF THINGSIJNSA Journal
The idea to connect everything to anything and at any point of time is what vaguely defines the concept of
the Internet of Things (IoT). The IoT is not only about providing connectivity but also facilitating
interaction among these connected things. Though the term IoT was introduced in 1999 but has drawn
significant attention during the past few years, the pace at which new devices are being integrated into the
system will profoundly impact the world in a good way but also poses some severe queries about security
and privacy. IoT in its current form is susceptible to a multitudinous set of attacks. One of the most
significant concerns of IoT is to provide security assurance for the data exchange because data is
vulnerable to some attacks by the attackers at each layer of IoT. The IoT has a layered structure where
each layer provides a service. The security needs vary from layer to layer as each layer serves a different
purpose. This paper aims to analyze the various security and privacy threats related to IoT. Some attacks
have been discussed along with some existing and proposed countermeasures.
This document discusses trends in fog computing. It explores how fog computing addresses limitations of cloud computing for IoT applications by processing data closer to the edge. Machine learning is being integrated into fog computing to help manage resources and address challenges. Deep learning integrated with fog computing can improve security by detecting cyberattacks. Fog computing provides benefits over cloud for applications like storage as a service and building smart cities due to lower latency and reduced network usage. The document examines various studies on fog computing architectures, applications, and emerging technologies.
CICS: Cloud–Internet Communication Security Framework for the Internet of Sma...AlAtfat
This document proposes a Cloud-Internet Communication Security (CICS) framework to provide secure communication among smart devices connected to the internet. The framework has four layers - a presentation layer on smart devices, a communication security layer providing encryption/decryption, a ubiquitous network layer, and a cloud layer. The cloud layer collects encrypted data from devices, processes it, and stores it securely. This framework aims to address security challenges like attacks that could disrupt services or cause denial of service when smart devices communicate using cloud computing.
A review on orchestration distributed systems for IoT smart services in fog c...IJECEIAES
This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agenda.
SECURITY AND PRIVACY AWARE PROGRAMMING MODEL FOR IOT APPLICATIONS IN CLOUD EN...ijccsa
This document summarizes a research paper on privacy-preserving techniques for IoT data in cloud environments. It introduces two differential privacy algorithms: 1) Generic differential privacy (GenDP) which provides generalized privacy protection for homogeneous and heterogeneous IoT metadata through data portioning. 2) Cluster-based differential privacy which groups similar data into clusters before defining classifiers to validate privacy. The paper evaluates these techniques and finds the cluster-based approach offers better security than customized interactive algorithms while maintaining data utility. Overall, the study presents new differential privacy methods for anonymizing IoT metadata stored in the cloud.
A new algorithm to enhance security against cyber threats for internet of thi...IJECEIAES
One major problem is detecting the unsuitability of traffic caused by a distributed denial of services (DDoS) attack produced by third party nodes, such as smart phones and other handheld Wi-Fi devices. During the transmission between the devices, there are rising in the number of cyber attacks on systems by using negligible packets, which lead to suspension of the services between source and destination, and can find the vulnerabilities on the network. These vulnerable issues have led to a reduction in the reliability of networks and a reduction in consumer confidence. In this paper, we will introduce a new algorithm called rout attack with detection algorithm (RAWD) to reduce the affect of any attack by checking the packet injection, and to avoid number of cyber attacks being received by the destination and transferred through a determined path or alternative path based on the problem. The proposed algorithm will forward the real time traffic to the required destination from a new alternative backup path which is computed by it before the attacked occurred. The results have showed an improvement when the attack occurred and the alternative path has used to make sure the continuity of receiving the data to the main destination without any affection.
Internet of things: review, architecture and applicationsCSITiaesprime
Devices linked to the internet of things (IoT) may communicate with one another in several settings. Furthermore, rather of relying on an existing centralized system, users may develop their own network by using wireless capabilities. This kind of network is known as a wireless mobile ad hoc network. The mobile ad-hoc network (MANET) enables IoT devices to connect with one another in an unstructured networked environment. IoT devices may connect, establish linkages, and share data on a continuous basis. In this system, the cloud's purpose is to store and analyze data acquired from IoT devices. One of the most significant challenges in cloud computing has been identified as information security, and its resolution will result in an even bigger increase in cloud computing usage and popularity in the future. Finally, the goal of this project is to create a framework for facilitating communication between IoT devices in a Cloud and MANET context. Our major contribution is a ground-breaking research initiative that combines cloud computing with the MANET and connects the internet of things. This research might be used to the IoT in the future.
SECURITY& PRIVACY THREATS, ATTACKS AND COUNTERMEASURES IN INTERNET OF THINGSIJNSA Journal
The idea to connect everything to anything and at any point of time is what vaguely defines the concept of the Internet of Things (IoT). The IoT is not only about providing connectivity but also facilitating interaction among these connected things. Though the term IoT was introduced in 1999 but has drawn significant attention during the past few years, the pace at which new devices are being integrated into the system will profoundly impact the world in a good way but also poses some severe queries about security and privacy. IoT in its current form is susceptible to a multitudinous set of attacks. One of the most significant concerns of IoT is to provide security assurance for the data exchange because data is vulnerable to some attacks by the attackers at each layer of IoT. The IoT has a layered structure where each layer provides a service. The security needs vary from layer to layer as each layer serves a different purpose. This paper aims to analyze the various security and privacy threats related to IoT. Some attacks have been discussed along with some existing and proposed countermeasures.
SECURITY& PRIVACY THREATS, ATTACKS AND COUNTERMEASURES IN INTERNET OF THINGSIJNSA Journal
The idea to connect everything to anything and at any point of time is what vaguely defines the concept of
the Internet of Things (IoT). The IoT is not only about providing connectivity but also facilitating
interaction among these connected things. Though the term IoT was introduced in 1999 but has drawn
significant attention during the past few years, the pace at which new devices are being integrated into the
system will profoundly impact the world in a good way but also poses some severe queries about security
and privacy. IoT in its current form is susceptible to a multitudinous set of attacks. One of the most
significant concerns of IoT is to provide security assurance for the data exchange because data is
vulnerable to some attacks by the attackers at each layer of IoT. The IoT has a layered structure where
each layer provides a service. The security needs vary from layer to layer as each layer serves a different
purpose. This paper aims to analyze the various security and privacy threats related to IoT. Some attacks
have been discussed along with some existing and proposed countermeasures.
This document discusses trends in fog computing. It explores how fog computing addresses limitations of cloud computing for IoT applications by processing data closer to the edge. Machine learning is being integrated into fog computing to help manage resources and address challenges. Deep learning integrated with fog computing can improve security by detecting cyberattacks. Fog computing provides benefits over cloud for applications like storage as a service and building smart cities due to lower latency and reduced network usage. The document examines various studies on fog computing architectures, applications, and emerging technologies.
CICS: Cloud–Internet Communication Security Framework for the Internet of Sma...AlAtfat
This document proposes a Cloud-Internet Communication Security (CICS) framework to provide secure communication among smart devices connected to the internet. The framework has four layers - a presentation layer on smart devices, a communication security layer providing encryption/decryption, a ubiquitous network layer, and a cloud layer. The cloud layer collects encrypted data from devices, processes it, and stores it securely. This framework aims to address security challenges like attacks that could disrupt services or cause denial of service when smart devices communicate using cloud computing.
A review on orchestration distributed systems for IoT smart services in fog c...IJECEIAES
This paper provides a review of orchestration distributed systems for IoT smart services in fog computing. The cloud infrastructure alone cannot handle the flow of information with the abundance of data, devices and interactions. Thus, fog computing becomes a new paradigm to overcome the problem. One of the first challenges was to build the orchestration systems to activate the clouds and to execute tasks throughout the whole system that has to be considered to the situation in the large scale of geographical distance, heterogeneity and low latency to support the limitation of cloud computing. Some problems exist for orchestration distributed in fog computing are to fulfil with high reliability and low-delay requirements in the IoT applications system and to form a larger computer network like a fog network, at different geographic sites. This paper reviewed approximately 68 articles on orchestration distributed system for fog computing. The result shows the orchestration distribute system and some of the evaluation criteria for fog computing that have been compared in terms of Borg, Kubernetes, Swarm, Mesos, Aurora, heterogeneity, QoS management, scalability, mobility, federation, and interoperability. The significance of this study is to support the researcher in developing orchestration distributed systems for IoT smart services in fog computing focus on IR4.0 national agenda.
A Comprehensive Survey on Exiting Solution Approaches towards Security and Pr...IJECEIAES
‘Internet of Things (IoT)’emerged as an intelligent collaborative computation and communication between a set of objects capable of providing on-demand services to other objects anytime anywhere. A large-scale deployment of data-driven cloud applications as well as automated physical things such as embed electronics, software, sensors and network connectivity enables a joint ubiquitous and pervasive internet-based computing systems well capable of interacting with each other in an IoT. IoT, a well-known term and a growing trend in IT arena certainly bring a highly connected global network structure providing a lot of beneficial aspects to a user regarding business productivity, lifestyle improvement, government efficiency, etc. It also generates enormous heterogeneous and homogeneous data needed to be analyzed properly to get insight into valuable information. However, adoption of this new reality (i.e., IoT) by integrating it with the internet invites a certain challenges from security and privacy perspective. At present, a much effort has been put towards strengthening the security system in IoT still not yet found optimal solutions towards current security flaws. Therefore, the prime aim of this study is to investigate the qualitative aspects of the conventional security solution approaches in IoT. It also extracts some open research problems that could affect the future research track of IoT arena.
A MIDDLEWARE FOR THE INTERNET OF THINGSIJCNCJournal
The Internet of Things (IoT) connects everyday objects including a vast array of sensors, actuators, and smart devices, referred to as “things” to the Internet, in an intelligent and pervasive fashion. This connectivity gives rise to the possibility of using the tracking capabilities of things to impinge on the location privacy of users. Most of the existing management and location privacy protection solutions do not consider the low-cost and low-power requirements of things; or, they do not account for the heterogeneity, scalability, or autonomy of communications supported in the IoT. Moreover, these traditional solutions do not consider the case where a user wishes to control the granularity of the disclosed information based on
the context of their use (e.g. based on the time or the current location of the user). To fill this gap, a middleware, referred to as the Internet of Things Management Platform (IoT-MP) is proposed in this paper.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
This document discusses the vision of a cloud-centric Internet of Things. It describes how ubiquitous sensing through wireless sensor networks can measure environmental indicators across many areas of life. As these sensing devices proliferate in communicating networks, they create the Internet of Things by seamlessly blending sensors and actuators with our environment. This generates enormous amounts of data that must be stored, processed, and presented seamlessly through cloud computing as a unifying framework. The document outlines key enabling technologies like RFID, wireless sensor networks, and addressing schemes. It also discusses applications, challenges, and the future direction of cloud-based IoT.
Novel authentication framework for securing communication in internet-of-things IJECEIAES
Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats. The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes.
This document discusses challenges and techniques for securing Internet of Things (IoT) architecture. It begins with an introduction to IoT and outlines key challenges including privacy, security, scalability, and connectivity issues that arise from the large number of interconnected devices. The document then reviews literature on techniques for securing IoT, such as using network function virtualization (NFV) and information-centric networking (ICN). It describes several proposed secure IoT architectures in detail and compares different approaches. The document concludes by discussing future directions for securing IoT architecture.
THE INTERNET OF THINGS: NEW INTEROPERABILITY, MANAGEMENT AND SECURITY CHALLENGESIJNSA Journal
The Internet of Things (IoT) brings connectivity to about every objects found in the physical space. It extends connectivity to everyday objects. From connected fridges, cars and cities, the IoT creates opportunities in numerous domains. However, this increase in connectivity creates many prominent challenges. This paper provides a survey of some of the major issues challenging the widespread adoption of the IoT. Particularly, it focuses on the interoperability, management, security and privacy issues in the IoT. It is concluded that there is a need to develop a multifaceted technology approach to IoT security, management, and privacy.
THE INTERNET OF THINGS: NEW INTEROPERABILITY, MANAGEMENT AND SECURITY CHALLENGESIJNSA Journal
The Internet of Things (IoT) brings connectivity to about every objects found in the physical space. It extends connectivity to everyday objects. From connected fridges, cars and cities, the IoT creates opportunities in numerous domains. However, this increase in connectivity creates many prominent challenges. This paper provides a survey of some of the major issues challenging the widespread adoption of the IoT. Particularly, it focuses on the interoperability, management, security and privacy issues in the IoT. It is concluded that there is a need to develop a multifaceted technology approach to IoT security,
management, and privacy.
THE INTERNET OF THINGS: NEW INTEROPERABILITY, MANAGEMENT AND SECURITY CHALLENGESIJNSA Journal
The Internet of Things (IoT) brings connectivity to about every objects found in the physical space. It
extends connectivity to everyday objects. From connected fridges, cars and cities, the IoT creates
opportunities in numerous domains. However, this increase in connectivity creates many prominent
challenges. This paper provides a survey of some of the major issues challenging the widespread adoption
of the IoT. Particularly, it focuses on the interoperability, management, security and privacy issues in the
IoT. It is concluded that there is a need to develop a multifaceted technology approach to IoT security,
management, and privacy.
BIOMETRIC SMARTCARD AUTHENTICATION FOR FOG COMPUTINGIJNSA Journal
In the IoT scenario, things at the edge can create significantly large amounts of data. Fog Computing has recently emerged as the paradigm to address the needs of edge computing in the Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications. In a Fog Computing environment, much of the processing would take place closer to the edge in a router device, rather than having to be transmitted to the Fog. Authentication is an important issue for the security of fog computing since services are offered to massive-scale end users by front fog nodes.Fog computing faces new security and privacy challenges besides those inherited from cloud computing. Authentication helps to ensure and confirms a user's identity. The existing traditional password authentication does not provide enough security for the data and there have been instances when the password-based authentication has been manipulated to gain access into the data. Since the conventional methods such as passwords do not serve the purpose of data security, research worksare focused on biometric user authentication in fog computing environment. In this paper, we present biometric smartcard authentication to protect the fog computing environment.
BIOMETRIC SMARTCARD AUTHENTICATION FOR FOG COMPUTINGIJNSA Journal
In the IoT scenario, things at the edge can create significantly large amounts of data. Fog Computing has recently emerged as the paradigm to address the needs of edge computing in the Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications. In a Fog Computing environment, much of the processing would take place closer to the edge in a router device, rather than having to be transmitted to the Fog. Authentication is an important issue for the security of fog computing since services are offered to massive-scale end users by front fog nodes.Fog computing faces new security and privacy challenges besides those inherited from cloud computing. Authentication helps to ensure and confirms a user's identity. The existing traditional password authentication does not provide enough security for the data and there have been instances when the password-based authentication has been manipulated to gain access into the data. Since the conventional methods such as passwords do not serve the purpose of data security, research worksare focused on biometric user authentication in fog computing environment. In this paper, we present biometric smartcard authentication to protect the fog computing environment.
Efficient ECC-Based Authentication Scheme for Fog-Based IoT EnvironmentIJCNCJournal
The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
Efficient ECC-Based Authentication Scheme for Fog-Based IoT EnvironmentIJCNCJournal
The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
MULTI-ACCESS EDGE COMPUTING ARCHITECTURE AND SMART AGRICULTURE APPLICATION IN...ijmnct
The Ubiquitous Power Internet of Things (UPIoT) is a deep integration of the interconnected power
network and communication network, enabling full perception of the system status and business operations
for power production, transmission, and consumption. To address the challenges of real-time perception,
rapid response, and privacy protection, UPIoT can benefit from the use of edge computing technology.
Edge computing is a new and innovative computing architecture that enables quick and efficient
processing of data close to the source, bypassing network latency and bandwidth issues. By shifting
computing power to the edge of the network, edge computing reduces the strain on cloud computing
centers and decreases input response time for users. However, access latency can still be a bottleneck,
which may overshadow the benefits of edge computing, particularly for data-intensive services. While edge
computing offers promising solutions for the IoT network, there are still some issues to address, such as
security, incomplete data, and investment and maintenance costs. In this paper, researcher conducts a
comprehensive survey of edge computing and how edge device placement can improve performance in IoT
networks. The paper includes a comparative use case of smart agriculture edge computing
implementations and discusses the various challenges faced in implementing edge computing in the UPIoT
context. The results also aim to inspire new edge-based IoT security designs by providing a complete
review of IoT security solutions at the edge layer in UPIoT
The Role of Cloud-MANET Framework in the Internet of Things (IoT)AlAtfat
In the next generation of computing, Mobile ad-hoc network
(MANET) will play a very important role in the Internet of Things (IoT). The
MANET is a kind of wireless networks that are self-organizing and auto
connected in a decentralized system. Every device in MANET can be moved
freely from one location to another in any direction. They can create a network
with their neighbors’ smart devices and forward data to another device. The IoTCloud-MANET framework of smart devices is composed of IoT, cloud
computing, and MANET. This framework can access and deliver cloud services
to the MANET users through their smart devices in the IoT framework where all
computations, data handling, and resource management are performed. The smart
devices can move from one location to another within the range of the MANET
network. Various MANETs can connect to the same cloud, they can use cloud
service in a real time. For connecting the smart device of MANET to cloud needs
integration with mobile apps. My main contribution in this research links a new
methodology for providing secure communication on the internet of smart
devices using MANET Concept in 5G. The research methodology uses the
correct and efficient simulation of the desired study and can be implemented in a
framework of the Internet of Things in 5G.
IS THERE A TROJAN! : LITERATURE SURVEY AND CRITICAL EVALUATION OF THE LATEST ...IJCI JOURNAL
IoT as a domain has grown so much in the last few years that it rivals that of the mobile network
environments in terms of data volumes as well as cybersecurity threats. The confidentiality and privacy of
data within IoT environments have become very important areas of security research within the last few
years. More and more security experts are interested in designing robust IDS systems to protect IoT
environments as a supplement to the more traditional security methods. Given that IoT devices are
resource-constrained and have a heterogeneous protocol stack, most traditional intrusion detection
approaches don’t work well within these schematic boundaries. This has led security researchers to
innovate at the intersection of Machine Learning and IDS to solve the shortcomings of non-learning based
IDS systems in the IoT ecosystem.
Efficient network management and security in 5G enabled internet of things us...IJECEIAES
The rise of fifth generation (5G) networks and the proliferation of internet- of-things (IoT) devices have created new opportunities for innovation and increased connectivity. However, this growth has also brought forth several challenges related to network management and security. Based on the review of literature it has been identified that majority of existing research work are limited to either addressing the network management issue or security concerns. In this paper, the proposed work has presented an integrated framework to address both network management and security concerns in 5G internet-of-things (IoT) network using a deep learning algorithm. Firstly, a joint approach of attention mechanism and long short-term memory (LSTM) model is proposed to forecast network traffic and optimization of network resources in a, service-based and user-oriented manner. The second contribution is development of reliable network attack detection system using autoencoder mechanism. Finally, a contextual model of 5G-IoT is discussed to demonstrate the scope of the proposed models quantifying the network behavior to drive predictive decision making in network resources and attack detection with performance guarantees. The experiments are conducted with respect to various statistical error analysis and other performance indicators to assess prediction capability of both traffic forecasting and attack detection model.
Internet of Things (IoT) plays a vital role in our
day to day life and normally used in our houses, in industry,
schools and in hospitals which implemented outside to manage
and control for taking report the changes in location prevent
from dangers and many more favorable things. Moreover all
other advantages can approach of big risks of privacy loss and
security issues. To protect the IoT devices, so many research
works have been measure to find those problems and locate a
best way to eradicate those risks or at least to reduce their effect
on the security and privacy requirement. Formation the concept
of device to device (D2D) communication technology, IoT plays
the information transfer from one end to another end as node of
interconnection. This paper examines the constraints and
security challenges posed by IoT connected devices and the
ability to connect, communicate with, and remotely manage an
incalculable number of networked, automated devices via the
Internet is becoming pervasive.
CONTEXT INFORMATION AGGREGATION MECHANISM BASED ON BLOOM FILTERS (CIA-BF) FOR...IJCNCJournal
Internet of Things (IoT) has become a popular technology in recent years. Different IoT applications such
as traffic control, environment monitoring, etc. contain many sensor devices, routers, actuators, edge
routers, and Base Stations (BS) which communicate with each other and send millions of data packets that
need to be delivered to their destination nodes successfully to ensure the High-performance communication
networks. IoT devices connect to the Internet using wired or wireless communication channels where most
of the devices are wearable, which means people slowly move from one point to another or fast-moving
using vehicles. How to ensure high performance of IoT data networks is an important research challenge
while considering the limitation of some IoT devices that may have limited power resources or limited
coverage areas. Many Kinds of research focus on how to customize routing protocols to be efficient for
IoT devices. The traditional routing mechanisms utilized specific IP addresses to identify users while in IoT
it is more beneficial to identify a group of users (things) based on any contexts, status, or values of their
resources such as the level of their batteries (e.g., low, medium or high). While IoT devices have different
characteristics, a multicasting mechanism to send one message to various groups of devices will not be
efficient in IoT communication networks since the aggregation of packets is very difficult. Thus, it is useful
to propose a mechanism that able to filter data packets that need to be sent to a specific group of devices.
In this paper, we propose efficient context-aware addressing mechanism, which is based on bloom filters
to increase the performance of IoT communication networks. A routing architecture is built based on
bloom filters which store routing information. In our works, we reduce the size of routing information
using a proposed aggregation mechanism which is based on connecting each group of IoT devices with an
edge router which is hierarchically connected to an upper router after operating its bloom filter. Our
simulation results show a significant improvement in the IoT performance metrics such as packets
transmission delay, jitter the throughput, packets dropping ratio, and the energy consumption in
comparison with well-known routing protocols of IoT such as Destination Sequenced Distance Vector
routing protocol (DSDV), and Ad hoc On-demand Distance Vector routing protocol (AODV).
Context Information Aggregation Mechanism Based on Bloom Filters (CIA-BF) for...IJCNCJournal
Internet of Things (IoT) has become a popular technology in recent years. Different IoT applications such as traffic control, environment monitoring, etc. contain many sensor devices, routers, actuators, edge routers, and Base Stations (BS) which communicate with each other and send millions of data packets that need to be delivered to their destination nodes successfully to ensure the High-performance communication networks. IoT devices connect to the Internet using wired or wireless communication channels where most of the devices are wearable, which means people slowly move from one point to another or fast-moving using vehicles. How to ensure high performance of IoT data networks is an important research challenge while considering the limitation of some IoT devices that may have limited power resources or limited coverage areas. Many Kinds of research focus on how to customize routing protocols to be efficient for IoT devices. The traditional routing mechanisms utilized specific IP addresses to identify users while in IoT it is more beneficial to identify a group of users (things) based on any contexts, status, or values of their resources such as the level of their batteries (e.g., low, medium or high). While IoT devices have different characteristics, a multicasting mechanism to send one message to various groups of devices will not be efficient in IoT communication networks since the aggregation of packets is very difficult. Thus, it is useful to propose a mechanism that able to filter data packets that need to be sent to a specific group of devices. In this paper, we propose efficient context-aware addressing mechanism, which is based on bloom filters to increase the performance of IoT communication networks. A routing architecture is built based on bloom filters which store routing information. In our works, we reduce the size of routing information using a proposed aggregation mechanism which is based on connecting each group of IoT devices with an edge router which is hierarchically connected to an upper router after operating its bloom filter. Our simulation results show a significant improvement in the IoT performance metrics such as packets transmission delay, jitter the throughput, packets dropping ratio, and the energy consumption in comparison with well-known routing protocols of IoT such as Destination Sequenced Distance Vector routing protocol (DSDV), and Ad hoc On-demand Distance Vector routing protocol (AODV).
Users Approach on Providing Feedback for Smart Home Devices – Phase IIijujournal
Smart Home technology has accomplished extraordinary success in making individuals' lives more straightforward and relaxing. Technology has recently brought about numerous savvy and refined frame works that advanced clever living innovation. In this paper, we will investigate the behavioral intention of user's approach to providing feedback for smart home devices. We will conduct an online survey for a sample of three to five students selected by simple random sampling to study the user's motto for giving feedback on smart home devices and their expectations. We have observed that most users are ready to actively share their input on smart home devices to improve the product's service and quality to fulfill the user’s needs and make their lives easier.
Users Approach on Providing Feedback for Smart Home Devices – Phase IIijujournal
Smart Home technology has accomplished extraordinary success in making individuals' lives more
straightforward and relaxing. Technology has recently brought about numerous savvy and refined frame
works that advanced clever living innovation. In this paper, we will investigate the behavioral intention of
user's approach to providing feedback for smart home devices. We will conduct an online survey for a
sample of three to five students selected by simple random sampling to study the user's motto for giving
feedback on smart home devices and their expectations. We have observed that most users are ready to
actively share their input on smart home devices to improve the product's service and quality to fulfill the
user’s needs and make their lives easier.
More Related Content
Similar to AUTHENTICATING DEVICES IN FOG-MOBILE EDGE COMPUTING ENVIRONMENTS THROUGH A WIRELESS GRID RESOURCE SHARING PROTOCOL
A Comprehensive Survey on Exiting Solution Approaches towards Security and Pr...IJECEIAES
‘Internet of Things (IoT)’emerged as an intelligent collaborative computation and communication between a set of objects capable of providing on-demand services to other objects anytime anywhere. A large-scale deployment of data-driven cloud applications as well as automated physical things such as embed electronics, software, sensors and network connectivity enables a joint ubiquitous and pervasive internet-based computing systems well capable of interacting with each other in an IoT. IoT, a well-known term and a growing trend in IT arena certainly bring a highly connected global network structure providing a lot of beneficial aspects to a user regarding business productivity, lifestyle improvement, government efficiency, etc. It also generates enormous heterogeneous and homogeneous data needed to be analyzed properly to get insight into valuable information. However, adoption of this new reality (i.e., IoT) by integrating it with the internet invites a certain challenges from security and privacy perspective. At present, a much effort has been put towards strengthening the security system in IoT still not yet found optimal solutions towards current security flaws. Therefore, the prime aim of this study is to investigate the qualitative aspects of the conventional security solution approaches in IoT. It also extracts some open research problems that could affect the future research track of IoT arena.
A MIDDLEWARE FOR THE INTERNET OF THINGSIJCNCJournal
The Internet of Things (IoT) connects everyday objects including a vast array of sensors, actuators, and smart devices, referred to as “things” to the Internet, in an intelligent and pervasive fashion. This connectivity gives rise to the possibility of using the tracking capabilities of things to impinge on the location privacy of users. Most of the existing management and location privacy protection solutions do not consider the low-cost and low-power requirements of things; or, they do not account for the heterogeneity, scalability, or autonomy of communications supported in the IoT. Moreover, these traditional solutions do not consider the case where a user wishes to control the granularity of the disclosed information based on
the context of their use (e.g. based on the time or the current location of the user). To fill this gap, a middleware, referred to as the Internet of Things Management Platform (IoT-MP) is proposed in this paper.
Research Inventy : International Journal of Engineering and Scienceinventy
Research Inventy : International Journal of Engineering and Science is published by the group of young academic and industrial researchers with 12 Issues per year. It is an online as well as print version open access journal that provides rapid publication (monthly) of articles in all areas of the subject such as: civil, mechanical, chemical, electronic and computer engineering as well as production and information technology. The Journal welcomes the submission of manuscripts that meet the general criteria of significance and scientific excellence. Papers will be published by rapid process within 20 days after acceptance and peer review process takes only 7 days. All articles published in Research Inventy will be peer-reviewed.
This document discusses the vision of a cloud-centric Internet of Things. It describes how ubiquitous sensing through wireless sensor networks can measure environmental indicators across many areas of life. As these sensing devices proliferate in communicating networks, they create the Internet of Things by seamlessly blending sensors and actuators with our environment. This generates enormous amounts of data that must be stored, processed, and presented seamlessly through cloud computing as a unifying framework. The document outlines key enabling technologies like RFID, wireless sensor networks, and addressing schemes. It also discusses applications, challenges, and the future direction of cloud-based IoT.
Novel authentication framework for securing communication in internet-of-things IJECEIAES
Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats. The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes.
This document discusses challenges and techniques for securing Internet of Things (IoT) architecture. It begins with an introduction to IoT and outlines key challenges including privacy, security, scalability, and connectivity issues that arise from the large number of interconnected devices. The document then reviews literature on techniques for securing IoT, such as using network function virtualization (NFV) and information-centric networking (ICN). It describes several proposed secure IoT architectures in detail and compares different approaches. The document concludes by discussing future directions for securing IoT architecture.
THE INTERNET OF THINGS: NEW INTEROPERABILITY, MANAGEMENT AND SECURITY CHALLENGESIJNSA Journal
The Internet of Things (IoT) brings connectivity to about every objects found in the physical space. It extends connectivity to everyday objects. From connected fridges, cars and cities, the IoT creates opportunities in numerous domains. However, this increase in connectivity creates many prominent challenges. This paper provides a survey of some of the major issues challenging the widespread adoption of the IoT. Particularly, it focuses on the interoperability, management, security and privacy issues in the IoT. It is concluded that there is a need to develop a multifaceted technology approach to IoT security, management, and privacy.
THE INTERNET OF THINGS: NEW INTEROPERABILITY, MANAGEMENT AND SECURITY CHALLENGESIJNSA Journal
The Internet of Things (IoT) brings connectivity to about every objects found in the physical space. It extends connectivity to everyday objects. From connected fridges, cars and cities, the IoT creates opportunities in numerous domains. However, this increase in connectivity creates many prominent challenges. This paper provides a survey of some of the major issues challenging the widespread adoption of the IoT. Particularly, it focuses on the interoperability, management, security and privacy issues in the IoT. It is concluded that there is a need to develop a multifaceted technology approach to IoT security,
management, and privacy.
THE INTERNET OF THINGS: NEW INTEROPERABILITY, MANAGEMENT AND SECURITY CHALLENGESIJNSA Journal
The Internet of Things (IoT) brings connectivity to about every objects found in the physical space. It
extends connectivity to everyday objects. From connected fridges, cars and cities, the IoT creates
opportunities in numerous domains. However, this increase in connectivity creates many prominent
challenges. This paper provides a survey of some of the major issues challenging the widespread adoption
of the IoT. Particularly, it focuses on the interoperability, management, security and privacy issues in the
IoT. It is concluded that there is a need to develop a multifaceted technology approach to IoT security,
management, and privacy.
BIOMETRIC SMARTCARD AUTHENTICATION FOR FOG COMPUTINGIJNSA Journal
In the IoT scenario, things at the edge can create significantly large amounts of data. Fog Computing has recently emerged as the paradigm to address the needs of edge computing in the Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications. In a Fog Computing environment, much of the processing would take place closer to the edge in a router device, rather than having to be transmitted to the Fog. Authentication is an important issue for the security of fog computing since services are offered to massive-scale end users by front fog nodes.Fog computing faces new security and privacy challenges besides those inherited from cloud computing. Authentication helps to ensure and confirms a user's identity. The existing traditional password authentication does not provide enough security for the data and there have been instances when the password-based authentication has been manipulated to gain access into the data. Since the conventional methods such as passwords do not serve the purpose of data security, research worksare focused on biometric user authentication in fog computing environment. In this paper, we present biometric smartcard authentication to protect the fog computing environment.
BIOMETRIC SMARTCARD AUTHENTICATION FOR FOG COMPUTINGIJNSA Journal
In the IoT scenario, things at the edge can create significantly large amounts of data. Fog Computing has recently emerged as the paradigm to address the needs of edge computing in the Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications. In a Fog Computing environment, much of the processing would take place closer to the edge in a router device, rather than having to be transmitted to the Fog. Authentication is an important issue for the security of fog computing since services are offered to massive-scale end users by front fog nodes.Fog computing faces new security and privacy challenges besides those inherited from cloud computing. Authentication helps to ensure and confirms a user's identity. The existing traditional password authentication does not provide enough security for the data and there have been instances when the password-based authentication has been manipulated to gain access into the data. Since the conventional methods such as passwords do not serve the purpose of data security, research worksare focused on biometric user authentication in fog computing environment. In this paper, we present biometric smartcard authentication to protect the fog computing environment.
Efficient ECC-Based Authentication Scheme for Fog-Based IoT EnvironmentIJCNCJournal
The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
Efficient ECC-Based Authentication Scheme for Fog-Based IoT EnvironmentIJCNCJournal
The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
MULTI-ACCESS EDGE COMPUTING ARCHITECTURE AND SMART AGRICULTURE APPLICATION IN...ijmnct
The Ubiquitous Power Internet of Things (UPIoT) is a deep integration of the interconnected power
network and communication network, enabling full perception of the system status and business operations
for power production, transmission, and consumption. To address the challenges of real-time perception,
rapid response, and privacy protection, UPIoT can benefit from the use of edge computing technology.
Edge computing is a new and innovative computing architecture that enables quick and efficient
processing of data close to the source, bypassing network latency and bandwidth issues. By shifting
computing power to the edge of the network, edge computing reduces the strain on cloud computing
centers and decreases input response time for users. However, access latency can still be a bottleneck,
which may overshadow the benefits of edge computing, particularly for data-intensive services. While edge
computing offers promising solutions for the IoT network, there are still some issues to address, such as
security, incomplete data, and investment and maintenance costs. In this paper, researcher conducts a
comprehensive survey of edge computing and how edge device placement can improve performance in IoT
networks. The paper includes a comparative use case of smart agriculture edge computing
implementations and discusses the various challenges faced in implementing edge computing in the UPIoT
context. The results also aim to inspire new edge-based IoT security designs by providing a complete
review of IoT security solutions at the edge layer in UPIoT
The Role of Cloud-MANET Framework in the Internet of Things (IoT)AlAtfat
In the next generation of computing, Mobile ad-hoc network
(MANET) will play a very important role in the Internet of Things (IoT). The
MANET is a kind of wireless networks that are self-organizing and auto
connected in a decentralized system. Every device in MANET can be moved
freely from one location to another in any direction. They can create a network
with their neighbors’ smart devices and forward data to another device. The IoTCloud-MANET framework of smart devices is composed of IoT, cloud
computing, and MANET. This framework can access and deliver cloud services
to the MANET users through their smart devices in the IoT framework where all
computations, data handling, and resource management are performed. The smart
devices can move from one location to another within the range of the MANET
network. Various MANETs can connect to the same cloud, they can use cloud
service in a real time. For connecting the smart device of MANET to cloud needs
integration with mobile apps. My main contribution in this research links a new
methodology for providing secure communication on the internet of smart
devices using MANET Concept in 5G. The research methodology uses the
correct and efficient simulation of the desired study and can be implemented in a
framework of the Internet of Things in 5G.
IS THERE A TROJAN! : LITERATURE SURVEY AND CRITICAL EVALUATION OF THE LATEST ...IJCI JOURNAL
IoT as a domain has grown so much in the last few years that it rivals that of the mobile network
environments in terms of data volumes as well as cybersecurity threats. The confidentiality and privacy of
data within IoT environments have become very important areas of security research within the last few
years. More and more security experts are interested in designing robust IDS systems to protect IoT
environments as a supplement to the more traditional security methods. Given that IoT devices are
resource-constrained and have a heterogeneous protocol stack, most traditional intrusion detection
approaches don’t work well within these schematic boundaries. This has led security researchers to
innovate at the intersection of Machine Learning and IDS to solve the shortcomings of non-learning based
IDS systems in the IoT ecosystem.
Efficient network management and security in 5G enabled internet of things us...IJECEIAES
The rise of fifth generation (5G) networks and the proliferation of internet- of-things (IoT) devices have created new opportunities for innovation and increased connectivity. However, this growth has also brought forth several challenges related to network management and security. Based on the review of literature it has been identified that majority of existing research work are limited to either addressing the network management issue or security concerns. In this paper, the proposed work has presented an integrated framework to address both network management and security concerns in 5G internet-of-things (IoT) network using a deep learning algorithm. Firstly, a joint approach of attention mechanism and long short-term memory (LSTM) model is proposed to forecast network traffic and optimization of network resources in a, service-based and user-oriented manner. The second contribution is development of reliable network attack detection system using autoencoder mechanism. Finally, a contextual model of 5G-IoT is discussed to demonstrate the scope of the proposed models quantifying the network behavior to drive predictive decision making in network resources and attack detection with performance guarantees. The experiments are conducted with respect to various statistical error analysis and other performance indicators to assess prediction capability of both traffic forecasting and attack detection model.
Internet of Things (IoT) plays a vital role in our
day to day life and normally used in our houses, in industry,
schools and in hospitals which implemented outside to manage
and control for taking report the changes in location prevent
from dangers and many more favorable things. Moreover all
other advantages can approach of big risks of privacy loss and
security issues. To protect the IoT devices, so many research
works have been measure to find those problems and locate a
best way to eradicate those risks or at least to reduce their effect
on the security and privacy requirement. Formation the concept
of device to device (D2D) communication technology, IoT plays
the information transfer from one end to another end as node of
interconnection. This paper examines the constraints and
security challenges posed by IoT connected devices and the
ability to connect, communicate with, and remotely manage an
incalculable number of networked, automated devices via the
Internet is becoming pervasive.
CONTEXT INFORMATION AGGREGATION MECHANISM BASED ON BLOOM FILTERS (CIA-BF) FOR...IJCNCJournal
Internet of Things (IoT) has become a popular technology in recent years. Different IoT applications such
as traffic control, environment monitoring, etc. contain many sensor devices, routers, actuators, edge
routers, and Base Stations (BS) which communicate with each other and send millions of data packets that
need to be delivered to their destination nodes successfully to ensure the High-performance communication
networks. IoT devices connect to the Internet using wired or wireless communication channels where most
of the devices are wearable, which means people slowly move from one point to another or fast-moving
using vehicles. How to ensure high performance of IoT data networks is an important research challenge
while considering the limitation of some IoT devices that may have limited power resources or limited
coverage areas. Many Kinds of research focus on how to customize routing protocols to be efficient for
IoT devices. The traditional routing mechanisms utilized specific IP addresses to identify users while in IoT
it is more beneficial to identify a group of users (things) based on any contexts, status, or values of their
resources such as the level of their batteries (e.g., low, medium or high). While IoT devices have different
characteristics, a multicasting mechanism to send one message to various groups of devices will not be
efficient in IoT communication networks since the aggregation of packets is very difficult. Thus, it is useful
to propose a mechanism that able to filter data packets that need to be sent to a specific group of devices.
In this paper, we propose efficient context-aware addressing mechanism, which is based on bloom filters
to increase the performance of IoT communication networks. A routing architecture is built based on
bloom filters which store routing information. In our works, we reduce the size of routing information
using a proposed aggregation mechanism which is based on connecting each group of IoT devices with an
edge router which is hierarchically connected to an upper router after operating its bloom filter. Our
simulation results show a significant improvement in the IoT performance metrics such as packets
transmission delay, jitter the throughput, packets dropping ratio, and the energy consumption in
comparison with well-known routing protocols of IoT such as Destination Sequenced Distance Vector
routing protocol (DSDV), and Ad hoc On-demand Distance Vector routing protocol (AODV).
Context Information Aggregation Mechanism Based on Bloom Filters (CIA-BF) for...IJCNCJournal
Internet of Things (IoT) has become a popular technology in recent years. Different IoT applications such as traffic control, environment monitoring, etc. contain many sensor devices, routers, actuators, edge routers, and Base Stations (BS) which communicate with each other and send millions of data packets that need to be delivered to their destination nodes successfully to ensure the High-performance communication networks. IoT devices connect to the Internet using wired or wireless communication channels where most of the devices are wearable, which means people slowly move from one point to another or fast-moving using vehicles. How to ensure high performance of IoT data networks is an important research challenge while considering the limitation of some IoT devices that may have limited power resources or limited coverage areas. Many Kinds of research focus on how to customize routing protocols to be efficient for IoT devices. The traditional routing mechanisms utilized specific IP addresses to identify users while in IoT it is more beneficial to identify a group of users (things) based on any contexts, status, or values of their resources such as the level of their batteries (e.g., low, medium or high). While IoT devices have different characteristics, a multicasting mechanism to send one message to various groups of devices will not be efficient in IoT communication networks since the aggregation of packets is very difficult. Thus, it is useful to propose a mechanism that able to filter data packets that need to be sent to a specific group of devices. In this paper, we propose efficient context-aware addressing mechanism, which is based on bloom filters to increase the performance of IoT communication networks. A routing architecture is built based on bloom filters which store routing information. In our works, we reduce the size of routing information using a proposed aggregation mechanism which is based on connecting each group of IoT devices with an edge router which is hierarchically connected to an upper router after operating its bloom filter. Our simulation results show a significant improvement in the IoT performance metrics such as packets transmission delay, jitter the throughput, packets dropping ratio, and the energy consumption in comparison with well-known routing protocols of IoT such as Destination Sequenced Distance Vector routing protocol (DSDV), and Ad hoc On-demand Distance Vector routing protocol (AODV).
Similar to AUTHENTICATING DEVICES IN FOG-MOBILE EDGE COMPUTING ENVIRONMENTS THROUGH A WIRELESS GRID RESOURCE SHARING PROTOCOL (20)
Users Approach on Providing Feedback for Smart Home Devices – Phase IIijujournal
Smart Home technology has accomplished extraordinary success in making individuals' lives more straightforward and relaxing. Technology has recently brought about numerous savvy and refined frame works that advanced clever living innovation. In this paper, we will investigate the behavioral intention of user's approach to providing feedback for smart home devices. We will conduct an online survey for a sample of three to five students selected by simple random sampling to study the user's motto for giving feedback on smart home devices and their expectations. We have observed that most users are ready to actively share their input on smart home devices to improve the product's service and quality to fulfill the user’s needs and make their lives easier.
Users Approach on Providing Feedback for Smart Home Devices – Phase IIijujournal
Smart Home technology has accomplished extraordinary success in making individuals' lives more
straightforward and relaxing. Technology has recently brought about numerous savvy and refined frame
works that advanced clever living innovation. In this paper, we will investigate the behavioral intention of
user's approach to providing feedback for smart home devices. We will conduct an online survey for a
sample of three to five students selected by simple random sampling to study the user's motto for giving
feedback on smart home devices and their expectations. We have observed that most users are ready to
actively share their input on smart home devices to improve the product's service and quality to fulfill the
user’s needs and make their lives easier.
October 2023-Top Cited Articles in IJU.pdfijujournal
International Journal of Ubiquitous Computing (IJU) is a quarterly open access peer-reviewed journal that provides excellent international forum for sharing knowledge and results in theory, methodology and applications of ubiquitous computing. Current information age is witnessing a dramatic use of digital and electronic devices in the workplace and beyond. Ubiquitous Computing presents a rather arduous requirement of robustness, reliability and availability to the end user. Ubiquitous computing has received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational applications in real life. The aim of the journal is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
ACCELERATION DETECTION OF LARGE (PROBABLY) PRIME NUMBERSijujournal
This document discusses methods for efficiently generating large prime numbers for use in RSA cryptography. It presents experimental results measuring the time taken to generate prime numbers when trial dividing the starting number by different numbers of initial primes before applying the Miller-Rabin primality test. The optimal number of trial divisions can be estimated as B=E/D, where E is the time for Miller-Rabin test and D is the maximum usefulness of trial division. Experimental results on different sized numbers support dividing by around 20 initial primes as optimal.
A novel integrated approach for handling anomalies in RFID dataijujournal
Radio Frequency Identification (RFID) is a convenient technology employed in various applications. The
success of these RFID applications depends heavily on the quality of the data stream generated by RFID
readers. Due to various anomalies found predominantly in RFID data it limits the widespread adoption of
this technology. Our work is to eliminate the anomalies present in RFID data in an effective manner so that
it can be applied for high end applications. Our approach is a hybrid approach of middleware and
deferred because it is not always possible to remove all anomalies and redundancies in middleware. The
processing of other anomalies is deferred until the query time and cleaned by business rules. Experimental
results show that the proposed approach performs the cleaning in an effective manner compared to the
existing approaches.
UBIQUITOUS HEALTHCARE MONITORING SYSTEM USING INTEGRATED TRIAXIAL ACCELEROMET...ijujournal
Ubiquitous healthcare has become one of the prominent areas of research inorder to address the
challenges encountered in healthcare environment. In contribution to this area, this study developed a
system prototype that recommends diagonostic services based on physiological data collected in real time
from a distant patient. The prototype uses WBAN body sensors to be worn by the individual and an android
smart phone as a personal server. Physiological data is collected and uploaded to a Medical Health
Server (MHS) via GPRS/internet to be analysed. Our implemented prototype monitors the activity, location
and physiological data such as SpO2 and Heart Rate (HR) of the elderly and patients in rehabilitation. The
uploaded information can be accessed in real time by medical practitioners through a web application.
ENHANCING INDEPENDENT SENIOR LIVING THROUGH SMART HOME TECHNOLOGIESijujournal
The population of elderly folks is ballooning worldwide as people live longer. But getting older often
means declining health and trouble living solo. Smart home tech could keep an eye on old folks and get
help quickly when needed so they can stay independent. This paper looks at a system combining wireless
sensors, video watches, automation, resident monitoring, emergency detection, and remote access. Sensors
track health signs, activities, appliance use. Video analytics spot odd stuff like falls. Sensor fusion and
machine learning find normal patterns so wonks can see unhealthy changes and send alerts. Multi-channel
alerts reach caregivers and emergency folks. A LabVIEW can integrate devices and enables local and
remote oversight and can control and handle emergency responses. Benefits seem to be early illness clues,
quick help, less burden on caregivers, and optimized home settings. But will old folks use all this tech? Can
we prove it really helps folks live longer and better? More research on maximizing reliability and
evaluating real-world impacts is needed. But designed thoughtfully, smart homes could may profoundly
improve the aging experience.
HMR LOG ANALYZER: ANALYZE WEB APPLICATION LOGS OVER HADOOP MAPREDUCEijujournal
In today’s Internet world, log file analysis is becoming a necessary task for analyzing the customer’s
behavior in order to improve advertising and sales as well as for datasets like environment, medical,
banking system it is important to analyze the log data to get required knowledge from it. Web mining is the
process of discovering the knowledge from the web data. Log files are getting generated very fast at the
rate of 1-10 Mb/s per machine, a single data center can generate tens of terabytes of log data in a day.
These datasets are huge. In order to analyze such large datasets we need parallel processing system and
reliable data storage mechanism. Virtual database system is an effective solution for integrating the data
but it becomes inefficient for large datasets. The Hadoop framework provides reliable data storage by
Hadoop Distributed File System and MapReduce programming model which is a parallel processing
system for large datasets. Hadoop distributed file system breaks up input data and sends fractions of the
original data to several machines in hadoop cluster to hold blocks of data. This mechanism helps to
process log data in parallel using all the machines in the hadoop cluster and computes result efficiently.
The dominant approach provided by hadoop to “Store first query later”, loads the data to the Hadoop
Distributed File System and then executes queries written in Pig Latin. This approach reduces the response
time as well as the load on to the end system. This paper proposes a log analysis system using Hadoop
MapReduce which will provide accurate results in minimum response time.
SERVICE DISCOVERY – A SURVEY AND COMPARISONijujournal
The document summarizes and compares several major service discovery approaches. It provides an overview of service discovery objectives and techniques, then surveys prominent protocols including SLP, Jini, and UPnP. Each approach is analyzed based on features like service description, discovery architecture, announcement/query mechanisms, and how they handle service usage and dynamic network changes. The comparison aims to identify strengths and limitations to guide future research in improving service discovery.
SIX DEGREES OF SEPARATION TO IMPROVE ROUTING IN OPPORTUNISTIC NETWORKSijujournal
Opportunistic Networks are able to exploit social behavior to create connectivity opportunities. This
paradigm uses pair-wise contacts for routing messages between nodes. In this context we investigated if the
“six degrees of separation” conjecture of small-world networks can be used as a basis to route messages in
Opportunistic Networks. We propose a simple approach for routing that outperforms some popular
protocols in simulations that are carried out with real world traces using ONE simulator. We conclude that
static graph models are not suitable for underlay routing approaches in highly dynamic networks like
Opportunistic Networks without taking account of temporal factors such as time, duration and frequency of
previous encounters.
International Journal of Ubiquitous Computing (IJU)ijujournal
International Journal of Ubiquitous Computing (IJU) is a quarterly open access peer-reviewed journal that provides excellent international forum for sharing knowledge and results in theory, methodology and applications of ubiquitous computing. Current information age is witnessing a dramatic use of digital and electronic devices in the workplace and beyond. Ubiquitous Computing presents a rather arduous requirement of robustness, reliability and availability to the end user. Ubiquitous computing has received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational applications in real life. The aim of the journal is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
PERVASIVE COMPUTING APPLIED TO THE CARE OF PATIENTS WITH DEMENTIA IN HOMECARE...ijujournal
The aging population and the consequent increase in the incidence of dementias is causing many
challenges to health systems, mainly related to infrastructure, low services quality and high costs. One
solution is to provide the care at house of the patient, through of home care services. However, it is not a
trivial task, since a patient with dementia requires constant care and monitoring from a caregiver, who
suffers physical and emotional overload. In this context, this work presents an modelling for development of
pervasive systems aimed at helping the care of these patients in order to lessen the burden of the caregiver
while the patient continue to receive the necessary care.
A proposed Novel Approach for Sentiment Analysis and Opinion Miningijujournal
as the people are being dependent on internet the requirement of user view analysis is increasing
exponentially. Customer posts their experience and opinion about the product policy and services. But,
because of the massive volume of reviews, customers can’t read all reviews. In order to solve this problem,
a lot of research is being carried out in Opinion Mining. In order to solve this problem, a lot of research is
being carried out in Opinion Mining. Through the Opinion Mining, we can know about contents of whole
product reviews, Blogs are websites that allow one or more individuals to write about things they want to
share with other The valuable data contained in posts from a large number of users across geographic,
demographic and cultural boundaries provide a rich data source not only for commercial exploitation but
also for psychological & sociopolitical research. This paper tries to demonstrate the plausibility of the idea
through our clustering and classifying opinion mining experiment on analysis of blog posts on recent
product policy and services reviews. We are proposing a Nobel approach for analyzing the Review for the
customer opinion
International Journal of Ubiquitous Computing (IJU)ijujournal
International Journal of Ubiquitous Computing (IJU) is a quarterly open access peer-reviewed journal that provides excellent international forum for sharing knowledge and results in theory, methodology and applications of ubiquitous computing. Current information age is witnessing a dramatic use of digital and electronic devices in the workplace and beyond. Ubiquitous Computing presents a rather arduous requirement of robustness, reliability and availability to the end user. Ubiquitous computing has received a significant and sustained research interest in terms of designing and deploying large scale and high performance computational applications in real life. The aim of the journal is to provide a platform to the researchers and practitioners from both academia as well as industry to meet and share cutting-edge development in the field.
USABILITY ENGINEERING OF GAMES: A COMPARATIVE ANALYSIS OF MEASURING EXCITEMEN...ijujournal
Usability engineering and usability testing are concepts that continue to evolve. Interesting research studies
and new ideas come up every now and then. This paper tests the hypothesis of using an EDA-based
physiological measurements as a usability testing tool by considering three measures; which are observers‟
opinions, self-reported data and EDA-based physiological sensor data. These data were analyzed
comparatively and statistically. It concludes by discussing the findings that has been obtained from those
subjective and objective measures, which partially supports the hypothesis.
SECURED SMART SYSTEM DESING IN PERVASIVE COMPUTING ENVIRONMENT USING VCSijujournal
Ubiquitous Computing uses mobile phones or tiny devices for application development with sensors
embedded in mobile phones. The information generated by these devices is a big task in collection and
storage. For further, the data transmission to the intended destination is delay tolerant. In this paper, we
made an attempt to propose a new security algorithm for providing security to Pervasive Computing
Environment (PCE) system using Public-key Encryption (PKE) algorithm, Biometric Security (BS)
algorithm and Visual Cryptography Scheme (VCS) algorithm. In the proposed PCE monitoring system it
automates various home appliances using VCS and also provides security against intrusion using Zigbee
IEEE 802.15.4 based Sensor Network, GSM and Wi-Fi networks are embedded through a standard Home
gateway.
PERFORMANCE COMPARISON OF ROUTING PROTOCOLS IN MOBILE AD HOC NETWORKSijujournal
Routing protocols have an important role in any Mobile Ad Hoc Network (MANET). Researchers have
elaborated several routing protocols that possess different performance levels. In this paper we give a
performance evaluation of AODV, DSR, DSDV, OLSR and DYMO routing protocols in Mobile Ad Hoc
Networks (MANETS) to determine the best in different scenarios. We analyse these MANET routing
protocols by using NS-2 simulator. We specify how the Number of Nodes parameter influences their
performance. In this study, performance is calculated in terms of Packet Delivery Ratio, Average End to
End Delay, Normalised Routing Load and Average Throughput.
The document compares the performance of various optical character recognition (OCR) tools. It analyzes eight OCR tools - Online OCR, Free Online OCR, OCR Convert, Convert image to text.net, Free OCR, i2OCR, Free OCR to Word Convert, and Google Docs. The document provides sample outputs of each tool processing the same input image. It then evaluates the tools based on character accuracy, character error rate, special symbol accuracy, and special symbol error rate to determine which tools most accurately convert images to editable text.
Optical Character Recognition (OCR) is a technique, used to convert scanned image into editable text
format. Many different types of Optical Character Recognition (OCR) tools are commercially available
today; it is a useful and popular method for different types of applications. OCR can predict the accurate
result depends on text pre-processing and segmentation algorithms. Image quality is one of the most
important factors that improve quality of recognition in performing OCR tools. Images can be processed
independently (.png, .jpg, and .gif files) or in multi-page PDF documents (.pdf). The primary objective of
this work is to provide the overview of various Optical Character Recognition (OCR) tools and analyses of
their performance by applying the two factors of OCR tool performance i.e. accuracy and error rate.
DETERMINING THE NETWORK THROUGHPUT AND FLOW RATE USING GSR AND AAL2Rijujournal
In multi-radio wireless mesh networks, one node is eligible to transmit packets over multiple channels to
different destination nodes simultaneously. This feature of multi-radio wireless mesh network makes high
throughput for the network and increase the chance for multi path routing. This is because the multiple
channel availability for transmission decreases the probability of the most elegant problem called as
interference problem which is either of interflow and intraflow type. For avoiding the problem like
interference and maintaining the constant network performance or increasing the performance the WMN
need to consider the packet aggregation and packet forwarding. Packet aggregation is process of collecting
several packets ready for transmission and sending them to the intended recipient through the channel,
while the packet forwarding holds the hop-by-hop routing. But choosing the correct path among different
available multiple paths is most the important factor in the both case for a routing algorithm. Hence the
most challenging factor is to determine a forwarding strategy which will provide the schedule for each
node for transmission within the channel. In this research work we have tried to implement two forwarding
strategies for the multi path multi radio WMN as the approximate solution for the above said problem. We
have implemented Global State Routing (GSR) which will consider the packet forwarding concept and
Aggregation Aware Layer 2 Routing (AAL2R) which considers the both concept i.e. both packet forwarding
and packet aggregation. After the successful implementation the network performance has been measured
by means of simulation study.
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...alexjohnson7307
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Ivanti’s Patch Tuesday breakdown goes beyond patching your applications and brings you the intelligence and guidance needed to prioritize where to focus your attention first. Catch early analysis on our Ivanti blog, then join industry expert Chris Goettl for the Patch Tuesday Webinar Event. There we’ll do a deep dive into each of the bulletins and give guidance on the risks associated with the newly-identified vulnerabilities.
Driving Business Innovation: Latest Generative AI Advancements & Success StorySafe Software
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
Fueling AI with Great Data with Airbyte WebinarZilliz
This talk will focus on how to collect data from a variety of sources, leveraging this data for RAG and other GenAI use cases, and finally charting your course to productionalization.
Main news related to the CCS TSI 2023 (2023/1695)Jakub Marek
An English 🇬🇧 translation of a presentation to the speech I gave about the main changes brought by CCS TSI 2023 at the biggest Czech conference on Communications and signalling systems on Railways, which was held in Clarion Hotel Olomouc from 7th to 9th November 2023 (konferenceszt.cz). Attended by around 500 participants and 200 on-line followers.
The original Czech 🇨🇿 version of the presentation can be found here: https://www.slideshare.net/slideshow/hlavni-novinky-souvisejici-s-ccs-tsi-2023-2023-1695/269688092 .
The videorecording (in Czech) from the presentation is available here: https://youtu.be/WzjJWm4IyPk?si=SImb06tuXGb30BEH .
In the realm of cybersecurity, offensive security practices act as a critical shield. By simulating real-world attacks in a controlled environment, these techniques expose vulnerabilities before malicious actors can exploit them. This proactive approach allows manufacturers to identify and fix weaknesses, significantly enhancing system security.
This presentation delves into the development of a system designed to mimic Galileo's Open Service signal using software-defined radio (SDR) technology. We'll begin with a foundational overview of both Global Navigation Satellite Systems (GNSS) and the intricacies of digital signal processing.
The presentation culminates in a live demonstration. We'll showcase the manipulation of Galileo's Open Service pilot signal, simulating an attack on various software and hardware systems. This practical demonstration serves to highlight the potential consequences of unaddressed vulnerabilities, emphasizing the importance of offensive security practices in safeguarding critical infrastructure.
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...Jeffrey Haguewood
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
HCL Notes and Domino License Cost Reduction in the World of DLAUpanagenda
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
Dandelion Hashtable: beyond billion requests per second on a commodity serverAntonios Katsarakis
This slide deck presents DLHT, a concurrent in-memory hashtable. Despite efforts to optimize hashtables, that go as far as sacrificing core functionality, state-of-the-art designs still incur multiple memory accesses per request and block request processing in three cases. First, most hashtables block while waiting for data to be retrieved from memory. Second, open-addressing designs, which represent the current state-of-the-art, either cannot free index slots on deletes or must block all requests to do so. Third, index resizes block every request until all objects are copied to the new index. Defying folklore wisdom, DLHT forgoes open-addressing and adopts a fully-featured and memory-aware closed-addressing design based on bounded cache-line-chaining. This design offers lock-free index operations and deletes that free slots instantly, (2) completes most requests with a single memory access, (3) utilizes software prefetching to hide memory latencies, and (4) employs a novel non-blocking and parallel resizing. In a commodity server and a memory-resident workload, DLHT surpasses 1.6B requests per second and provides 3.5x (12x) the throughput of the state-of-the-art closed-addressing (open-addressing) resizable hashtable on Gets (Deletes).
GraphRAG for Life Science to increase LLM accuracyTomaz Bratanic
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
FREE A4 Cyber Security Awareness Posters-Social Engineering part 3Data Hops
Free A4 downloadable and printable Cyber Security, Social Engineering Safety and security Training Posters . Promote security awareness in the home or workplace. Lock them Out From training providers datahops.com
Taking AI to the Next Level in Manufacturing.pdfssuserfac0301
Read Taking AI to the Next Level in Manufacturing to gain insights on AI adoption in the manufacturing industry, such as:
1. How quickly AI is being implemented in manufacturing.
2. Which barriers stand in the way of AI adoption.
3. How data quality and governance form the backbone of AI.
4. Organizational processes and structures that may inhibit effective AI adoption.
6. Ideas and approaches to help build your organization's AI strategy.
TrustArc Webinar - 2024 Global Privacy SurveyTrustArc
How does your privacy program stack up against your peers? What challenges are privacy teams tackling and prioritizing in 2024?
In the fifth annual Global Privacy Benchmarks Survey, we asked over 1,800 global privacy professionals and business executives to share their perspectives on the current state of privacy inside and outside of their organizations. This year’s report focused on emerging areas of importance for privacy and compliance professionals, including considerations and implications of Artificial Intelligence (AI) technologies, building brand trust, and different approaches for achieving higher privacy competence scores.
See how organizational priorities and strategic approaches to data security and privacy are evolving around the globe.
This webinar will review:
- The top 10 privacy insights from the fifth annual Global Privacy Benchmarks Survey
- The top challenges for privacy leaders, practitioners, and organizations in 2024
- Key themes to consider in developing and maintaining your privacy program
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdfChart Kalyan
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providersakankshawande
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
AUTHENTICATING DEVICES IN FOG-MOBILE EDGE COMPUTING ENVIRONMENTS THROUGH A WIRELESS GRID RESOURCE SHARING PROTOCOL
1. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
DOI : 10.5121/iju.2022.13201 1
AUTHENTICATING DEVICES IN FOG-MOBILE EDGE
COMPUTING ENVIRONMENTS THROUGH A
WIRELESS GRID RESOURCE SHARING PROTOCOL
Tyson Brooks
Syracuse University, USA
ABSTRACT
The rapid growth of the Internet of Things (IoT), cloud computing, Fog computing, mobile edge computing
and wireless grids has resulted in the widespread deployment of relatively immature technology. These
technologies, which will primarily use 5G wireless communication networks, are becoming popular
because they can be deployed quickly with little infrastructure and lends themselves to environments
utilizing numerous internet connected devices (ICD). There are, however, many significant challenges
faced by security designers, engineers and implementers of these networks in ensuring that the level of
security afforded is appropriate. Because of the threat of exploitation, these networks have to be protected
by a robust security architecture due to these technologies being plagued with security problems. The
authentication of smart ICDs to IoT networks is a critical mechanism for achieving security on these new
information system platforms. This article identifies an authentication process required for these ICDs,
which will need to prove their identity to authenticate to an IoT fog-mobile edge computing (FMEC) cloud
network through a wireless grid authentication process. The purpose of this article is to begin to
hypothesize a generic authentication methodology for these FMEC clouds uses in an IoT architecture. The
proposed methodology, called wg-IoT, must include the integration of Fog computing, wireless grids and
mobile edge computing clouds to create this new IoT architecture. An authentication process developed
from the resource sharing protocol (RSP) from a wireless grid is first developed and proposed for the
authentication of ICDs. The wireless grid core components must be embedded in IoT devices or sensors
depending on their capability to handle five primary functions: management of identification [ID] and
presence, permissions management, data transferability, application-programming interface [API] and
security.
KEYWORDS
Wireless grids, authentication, fog computing, internet of things, mobile edge computing
1. INTRODUCTION
The IoT paradigm, which consist of a network of embedded sensor connected to the Internet, is
rapidly gaining ground in wireless telecommunications (Zhang et al. 2012). However, only
recently has the IoT market begun to experience rapid growth. This is due to several factors,
which include: the extensive spread of the Internet, next generation 5G networks, high
penetrations of mobile devices usage, new cloud computing platforms, fog-mobile edge
computing (FMEC) and microbrowsers1,2
. Industry analysts predict that the global IoT market
will reach $772.5B in 2018, attaining a Compound Annual Growth Rate (CAGR) of 14% through
the 2017-2021 forecast period - surpassing the $1 trillion mark in 2020 and reaching $1.1 trillion
1
https://www.transparencymarketresearch.com/mobile-edge-computing-market.html
2
https://www.ibm.com/developerworks/library/wa-browse/index.html
2. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
2
in 2021%3
. The Fog computing market is expected to reach $617.3Mil by 20254
and over $5.6B
devices will utilize mobile edge computing, primarily in the manufacturing, energy, and
transportation industries5
. All of these market forces are converging, which in turn is making the
IoT market increasingly data centric.
Any cloud network is subject to becoming the target of exploitation by individuals or groups
outside of the authorized group of intended users and/or devices (Firdous et al. 2017). In addition,
the advances in wireless technology have given the common individual the ability to establish a
communications connection with anyone at any time. This ability has created a general addiction
to connectedness and has opened new opportunities for the exploitation of communications. The
exploitation of a cloud network by adversaries is conducted for four main reasons; (1) to gain
access to data flowing over the network, (2) to disrupt the flow of data on the network, (3) to
parasitically usurp the networks resources (e.g. to use a network free of charge), and (4) provide
disinformation by injecting false data into the network in order to mislead and to cause confusion
and doubt (Gupta & Gupta, 2018; Ahmed et al. 2018). However, this situation has now changed,
as ICDs will be able to perform these exploitations with limited human interactions.
With these assumptions as background, authentication of [wireless] ICDs in these FMEC clouds
must provide strong encryption to prevent eavesdropping, and must deliver mutual authentication
to ensure that sensitive information is transmitted only over legitimate FMEC cloud networks.
Authentication will require that ICDs prove their identity through a hardware/software token, a
challenge/response mechanism or a combination of these and other methods of identification.
Authentication should be two-way, the ICD must authenticate to the network, and the network
should authenticate to the ICD. This lets the network know that it is communicating with a valid,
non-malicious ICD. By having the network authenticate to the ICD, it is less likely that an
unauthorized ICD will be able to pose as valid in the network. The purpose of this article is to
hypothesize a generic authentication methodology for ICDs in FMEC clouds utilizing the IoT
architecture.
2. FOG COMPUTING
Cisco, Inc., (2015b) defines the Fog as „an extension of the cloud to be closer to the things that
produce and act on IoT data, processing IoT data closer to where it is produced and needed solves
the challenges of exploding data volume, variety, and velocity and accelerating awareness and
response to IoT events by eliminating a round trip to the cloud for analysis‟. Iorga et al. (2018)
from the National Institute of Standards and Technology (2018) recently defined Fog computing
as:
A layered model for enabling ubiquitous access to a shared continuum of scalable computing
resources. The model facilitates the deployment of distributed, latency-aware applications and
services, and consists of fog nodes (physical or virtual), residing between smart end-devices and
centralized (cloud) services. The fog nodes are context aware and support a common data
management and communication system. They can be organized in clusters - either vertically (to
support isolation), horizontally (to support federation), or relative to fog nodes‟ latency-distance
to the smart end-devices. Fog computing minimizes the request-response time from/to supported
applications, and provides, for the end-devices, local computing resources and, when needed,
network connectivity to centralized services.
3
https://www.networkworld.com/article/3244927/internet-of-things/new-idc-report-forecasts-huge-growth-for-iot.html
4
https://www.grandviewresearch.com/press-release/global-fog-computing-market
5
https://www.thorntech.com/2017/11/edge-computing-and-the-cloud-future-of-iot/
3. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
3
The characteristics of the Fog (proximity and location awareness, geo-distribution, hierarchical
organization) make it the suitable platform to support both energy-constrained wireless grids
(Bonomi et al. 2012). However, this implies a number of characteristics that make the Fog a non-
trivial extension of the cloud including edge location, location awareness, and low latency (Zhu
et al. 2013). The Fog, for instance, will play an active role in delivering high quality streaming to
moving vehicles, through proxies and access points positioned along highways and tracks.
Localization of data processing is a fundamental and essential issue for operational wireless
sensor networks (WSNs) (Sheu et al. 2008).
A large number of Fog nodes, as a consequence of the wide geo-distribution, as evidenced in
sensor networks in general and the Smart Grid in particular will provide support for mobility
(Mukherjee et al. 2017; Ekanayake et al. 2018). It is essential for many Fog applications to
communicate directly with mobile devices, and therefore support mobility techniques, such as the
Locator ID Separation Protocol (LISP) 1, that decouple host identity from location identity, and
require a distributed directory system (Zhu et al. 2013). Support for on-line analytic and interplay
with the Cloud, the Fog is positioned to play a significant role in the ingestion and processing of
the data close to the source (Zhu et al. 2013). Figure 1 presents the idealized information and
computing architecture supporting the future IoT applications, and illustrates the role of Fog
computing through compute, storage, and networking resources building blocks of both the
Cloud, the Fog and the mobile edge of the network.
Figure 1. The Internet of Things and Fog Computing
(Source: Cisco 2015a; Brooks & McKnight, 2017)
3. WIRELESS GRIDS
As displayed in Figure 2, a wireless grid is an augmentation of a wired grid that facilitates the
exchange of information and the interaction between heterogeneous wireless devices (Agarwal et
al. 2004). The IoT is an integrated part of the future Internet including existing and evolving
Internet and network developments and could be conceptually defined as a dynamic global
network infrastructure with self-configuring capabilities (Vermesan et al. 2011). This is based on
standard and interoperable communication protocols where physical and virtual smart
“things/objects” (e.g. wireless sensors, actuators, radio frequency identification [RFID] tags,
smart mobile devices, mobile robots, etc.) have identities, physical attributes, and virtual
personalities, use intelligent interfaces, and are seamlessly integrated into the information
network (Vermesan et al. 2011). The application of wireless grids, FMEC and IoT architectures is
4. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
4
a key objective which facilitates information sharing and provides a means for the system to get
information (whether wired or wirelessly) to individuals to satisfy their needs.
Figure 2. WIGIT Open Framework
(Source: McKnight et al. 2015)
In the IoT, smart “things/objects” (i.e. internet connected devices or ICDs) are expected to
become active participants in business, information and social processes where they are enabled
to interact and communicate among themselves and with the environment by exchanging data
and information sensed about the environment (Vermesan et al. 2011; Uckelmann et al. 2011).
Services will be able to interact with these smart ICD‟s using standard interfaces that will provide
the necessary link via the Internet, to query and change their state and retrieve any information
associated with them, taking into account security and privacy issues (Vermesan et al. 2011).
„Things‟ can only become context aware, sense, communicate, interact, exchange data,
information and knowledge if they are suitably equipped with appropriate object-connected
technologies; unless of course they are human „things‟ or other entities with these intrinsic
capabilities (Brooks, 2017). In this vision, using intelligent decision-making algorithms in
software applications, appropriate rapid responses can be given to physical phenomena, based on
the very latest information collected about physical entities and consideration of patterns in the
historical data, either for the same entity or for similar entities (Yan et al. 2010; Vermesan et al.
2011).
However, the application of authentication of these ICD‟s within this environment brings about
new and challenging problems from an information security perspective. Traditional security
mechanisms, such as identification/authentication and access control (authorization) are
complicated in these environments, requiring new standards and the development of new
products. Counter-intuitively, the more wireless grids, FMECs and IoT architectures that exist,
the more vulnerable they will towards cyber-attacks. This is because, with wireless grids, FMECs
and IoT architectures, every user/device/thing/object may have the right to access the system
causing errors and flaws. For this reason, individual user/device/thing/objects will continue to be
the primary targets of malicious software (or malware) attacks.
4. WIRELESS GRID ‘EDGEWARE’
As displayed in Figure 2, Edgeware, a new class of software applications, enables the ad hoc
connection of people, devices, software and services in a personal cloud, supported by personal
cyber infrastructure (Brooks et al. 2013, McKnight et al. 2015). Edge devices are routers,
switches, routing switches, integrated access devices (IAD), multiplexers, and a variety of
metropolitan area network (MAN)/wide area network (WAN) access devices that provide entry
points into enterprise or carrier/service provider core networks which translate between one type
5. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
5
of network protocol and another (McKnight et al. 2015). Edgeware applications can dynamically
make use of content and resources present in devices - phones, laptops, PCs, cameras, printers,
screens, etc. – through connectivity via a wireless grid (McKnight et al. 2015).
Figure 3. Edgeware Grid Core
(Source: McKnight, ed. WiGiT v0.3)
The blue boxes on the right in Figure 2 represent Edgeware applications that sit on a user
interface, which in turn sits on an API [McKnight et al. 2015]. These may represent dozens or
hundreds of different sorts of mini- programs that enable different kinds of resource sharing and
functionality. Edgeware applications are typically delivered as a service; and come in 2 primary
varieties: Gridlets, that is, proprietary Edgeware applications, and Wiglets, that is, non-
proprietary open Edgeware applications (McKnight et al. 2015). Not all devices enabled on a
wireless grid need to have an Edgeware application sitting on them to be accessible and active.
The only thing that must be deployed for a wireless grid to work is for the Grid Core to be on
some intelligent machine, somewhere, with rights to control other „Edge‟ resources such as
sensors that may not have the capability to have the core components installed; which may be
facilitated by one or more Gridlets and/or Wiglets (McKnight et al. 2015). Other network
hardware, software, services, and content may be controlled and shared through the wireless grid
„Edgeware‟ as these may not be or cannot become self- aware devices on the grid; however, if
those „Edge‟ resources are in a relationship with other hardware, software, and services, which
are part of the wireless grid, they may function as if they were fully cognitive (McKnight et al.
2015) A further differentiation in the varieties of Edgeware applications may also be drawn
between peer-to-peer implementations, and cloud to edge applications, which may appear at first
glance to be a basic client-server implementation. In both cases, however, the Edgeware
application may be able to interact dynamically with other types of Edgeware applications.
Meaning, the architecture and open specifications presented here allow for ad hoc, peer-to-peer
applications and services to interact with cloud services (McKnight et al. 2015).
The Grid Core components are represented by the green box and embedded in certain devices or
sensors depending on their capability, which makes every device a node on the wireless grid
(McKnight et al. 2015). This core is extremely „light‟ and easy to embed on a wide range of
different kinds of equipment. McKnight et al. (2015) identified that users are allowed to share
and manage the digital resources at their fingertips through applications of the architecture‟s eight
core components:
6. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
6
the authentication and authorization component [AAC]
the billing, accounting and charging component [BAC] which provides access to the
things/objects financial information,
the messaging and presence component [MPC] which provides scalable messaging,
manages the availability of a thing/object and the method or language of communication
with that thing/object,
the metadata component [MC] which creates, edits, and generally manages the metadata
for an ICD, (5) the resource management component [RMC] which is responsible for
aggregating and searching metadata about things/objects within the context of
authentication and works closely with the AAC and MPC,
the economic and legal policy component [ELP] which supports economic and legal
policies,
the communication protocols component [CPC] which is a sub-system that manages the
interaction with specific types of resources, such as printers, files, etc. and is needed to
interact within a wireless grid, identifies and manages network and internetwork
communications including IP and other protocols (e.g. Bluetooth), provides connections
with other wireless grids and across the internet, and,
the security component.
The wireless grid architecture core components handle four primary functions, which make the
grid-enabled ecosystem possible: management of identification (ID) and presence, permissions
management, data transfer ability, and API/interfacing (McKnight et al. 2015). The layers above
the core are comprised of the API which enables connections with other applications and
services, the User Interface (which may or may not be necessary depending on the device upon
which it sits), and finally the Edgeware applications are shown in blue in Figure 2 (McKnight et
al. 2015).
Once a grid is established then resources can be published or accessed across the grid, enabling
the infinite functional possibilities of the Grid technology. There are three classes of wireless grid
applications (McKnight et al. 2015):
Class 1: Applications aggregating information from the range of input/output interfaces
found in nomadic and mobile devices,
Class 2: Applications utilizing the locational and contextual characteristics in which the
devices will be found and,
Class 3: Applications leveraging the mesh network capabilities of groups of devices:
Workplace-As-A-Service (WPaaS), Compute-Infrastructure-As-A-Service (CIaaS) and
Virtual Private Cloud (VPC) are reference architectures that potentially can meet the
unique requirements to satisfy enterprise-grade customers.
These wireless grid Edgeware systems give the user greater mobility and flexibility. Although
these characteristics of services provide a number of advantages especially towards its integration
into IoT architectures, they leave these wireless grids Edgeware devices vulnerable to attacks and
other security related problems (Brooks et al. 2013). It is exactly the mobile nature of the devices
that exposes it to greater risk of data loss or theft and this contrasts with the wired service, which
terminates in one location, such as in the home or office, making it more safeguarded (Brooks et
al. 2013). The trend of integrating these new complex systems with advanced computer and
communication technologies has introduced serious cyber-security concerns, especially in these
new architectures; where the environment will no longer be regarded as reliable to support
communications as before (Brooks et al. 2013). For example, due to the important role of the
smart grid as the key energy IoT infrastructure, the information infrastructure needed to route
7. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
7
data by providing the dynamic ad-hoc sharing of heterogonous devices and the need to protect its
information security is an extremely important task, which can significantly contribute to security
issues given the threat of cyber-attacks (Li et al. 2012). Traditional security mechanisms, such as
identification/authentication and access control (authorization) are complicated in these new
environments, requiring new standards and the development of new security products.
Due to its physical broadcast nature, these new communication networks are generally more
vulnerable to malicious and accidental threats than their wired counterparts (Covington &
Carskadden, 2013). As a result of this inherent vulnerability, security is a mandatory component.
While it is more difficult and potentially more important to secure this communication, the
issues, threats and the respective required services to adequately respond to these threats are
mostly the same for wired and wireless technology (Covington & Carskadden, 2013).
Alternatively, the task of providing security services for these networks is more complicated than
in wired networks. Power and bandwidth limitations, often non-existent in wired networks,
impose considerable constraints on the complexity and efficiency of security protocols
(Covington & Carskadden, 2013).
5. FOG MOBILE EDGE COMPUTING (FMEC)
A mobile grid combines mobile computing and grid computing and develops rapidly (Zeng et al.
2008). FMEC can be mobile, portable or fixed. However, in general, the mobile user unit is a
mobile, wireless device. These user devices provide one basic function – connectivity with an
access point or a base station providing mobile services. Samimi et al. (2006) define FMECs as
clouds that support autonomic communication at the wireless edge of the Internet, defined as
those nodes that are one, at most a few, wireless hops away from the wired infrastructure. FMEC
enable dynamic instantiation, composition, configuration, and reconfiguration of services on an
overlay network to support mobile computing (Samimi et al. 2006). FMEC provides a distributed
infrastructure designed to facilitate rapid prototyping and deployment of services that enhance
communication performance, robustness, and security and include a collection of low level
facilities that can be either invoked directly by applications or used to compose more complex
services (McKinley et al. 2006).
As displayed in Figure 3, the FMECs model supports dynamic composition and reconfiguration
of services to support clients at the wireless edge and provide an infrastructure for composing
autonomic communication services (Samimi et al. 2006; Vermesan et al. 2011). FMECs (see
Figure 3) allows information systems to mirror the integrated, evolving business processes of an
enterprise to deliver specific capabilities and service levels (Samimi et al. 2006). The ability of
FMECs to change, evolve, and manage business processes throughout an enterprise is changing
the way information technology development, integration and deployment works. Pervasive
FMECs in an enterprise will identify and highlight cross-functional dependencies and encourage
cooperation and communication between and among functional units and information technology
(Samimi et al. 2006).
8. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
8
Figure 4. Fog Mobile Edge Computing
(Source: Samimi et al. 2006)
Wireless grids are infrastructure-less mobile ad-hoc networks that can intelligently and
dynamically interconnect users and stakeholders at multiple sites, transfer digital media, assume
and respond to different equipment types, and adapt to low power conditions and diminished
communications capabilities (McKnight et al. 2004). There are two modes of wireless grid
creation, user mode and machine-based mode, as displayed in Figure 4 and Figure 5, compare a
„human-user‟-centric grid with a „node-based‟ grid (McKnight et al. 2015). In purely conceptual
terms, it is evident that in both cases the outermost frontier of what is currently possible (i.e.,
engaging the full range of user types) with device heterogeneity considered on an infinite axis
only goes so far; the promise of the wireless grid technology is the capability of „M2M‟
communication via a virtual distributed operating system that enables the IoT (McKnight et al.
2015).
Figure 5. User View
(Source: McKnight, ed. WiGiT v0.3)
Figure 6. Machine View
(Source: McKnight, ed. WiGiT v0.3)
The vision of the IoT will be driven by FMEC, wireless grids, Cloud computing and other
various technologies, which also include improving information reliability and efficiency and
enhancing customer participation. Given the obvious benefits of the IoT, its introduction has also
posed severe security concerns. As a critical infrastructure, the IoT is expected to be a tempting
9. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
9
target for hacking, service theft, sabotage, terrorism and other malicious attacks (Li et al. 2012).
IoT security has been widely recognized as a major issue with potentially catastrophic
implications. Due to the its heavy reliance on the cyber-infrastructure for sensing and control, the
IoT will be exposed to new risk from computer network vulnerabilities as well as inherit existing
risks from physical vulnerabilities within existing systems (Li et al. 2012). Because of the
significant role of the IoT as a key infrastructure, the cyber-attacks against it pose sever threats to
the security of the architecture.
Both cascading failures and collapses are catastrophic events and will finally lead to large-scale
shutdown of wireless grids, FMECs and IoT architectures. Therefore, the authentication of ICD‟s
will be key for wireless grids for the IoT architecture. An authentication model is needed to
analyze the wireless grid ICD‟s for the wg-IoT architecture. In general, the framework provides a
generic process for understanding the authentication and authorization component (AAC), the
messaging and presence component (MPC) and the security component (SC) from the RSP
(McKnight et al. 2015). In this chapter, the consideration is that the proposed framework can be
easily extended to analyze a coordinated authentication cyber-attacks launched by attacker‟s
trying to gain access to the overall IoT architecture.
6. CONCEPTUALIZATION OF AUTHENTICATION IN A FOG-MOBILE EDGE
COMPUTING ENVIRONMENT UTILIZING THE WIRELESS GRID
RESOURCE SHARING PROTOCOL
Authentication is an important issue for the security of fog computing since services are offered
to massive-scale end users by front fog nodes (Yi et al. 2015, August). Amor et al. (2017)
introduce of a mutual authentication between Fog users at the Edge of the network and the Fog
servers at the Fog layer proposing a fog user-fog server anonymous mutual authentication
scheme; in which the fog user and fog server authenticate each other and establish a session key
without disclosing user's real identity. This scheme is based on Pseudonym Based Cryptography
(PBC), Elliptic Curve Discrete Logarithm Problem (ECDLP) and bilinear pairing to establish the
session key (Amor et al. 2017). Alharbi et al. (2017) propose a Fog Computing-based Security
(FOCUS) system, which leverages a virtual private network (VPN) to secure the access channel
to IoT devices through a challenge-response authentication process to protect the VPN server
against distributed denial of service (DDoS) attacks. Furthermore, as the emergence of biometric
authentication, such as fingerprint authentication, face authentication, touch-based or keystroke-
based authentication etc, in mobile computing and cloud computing, applying biometric-based
authentication in fog computing will be beneficial (Yi et al. 2015, June).
Authentication requires that an ICD prove its identity. Authentication will require that the ICD
authenticate to the IoT network and the network should authenticate the ICD. The wireless grid
core components must be embedded in IoT devices or sensors depending on their capability to
handle five primary functions: (1) management of identification [ID] and presence, (2)
permissions management, (3) data transfer ability, (4) application programming interface [API]
and (4) security (McKnight et al. 2015). These elements make the grid-enabled ecosystem
possible and make every ICD a node on the wireless grid. The layers above the core are
comprised of the wireless grid‟s API, which enables connections with other applications and
services, the grid user interface (GUI), which may or may not be necessary depending on the
thing/object upon which it resides, and finally the wireless grid „Edgeware‟ applications, which
are typically delivered as services (McKnight et al. 2015) of resource sharing and functionality
services and once a wireless grid is established, then resources and services can be published or
accessed across the grid, enabling the infinite functional possibilities of wireless grid technology
(McKnight et al. 2015).
10. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
10
The wireless grid is made possible by the „Grid Core‟, which is software installed on any Grid-
enabled, IoT device (McKnight et al. 2015). As identified in Figure 7, the resource sharing
protocol (RSP) is the primary Grid Core function provided by the architecture‟s eight core
components: AAC, BAC, MPC, MC, RMC, ELP, CPC and SC (McKnight et al. 2015). The RSP
enables creating, joining and subscribing to a wireless grid through provision of the following
services: resource identification, resource acquisition, resource advertisement/discovery,
communication amongst wireless grids, communication with the internet, creating a wireless
grid, joining, and subscribing to a wireless grid (McKnight et al. 2015).
Figure 7. Open Wireless Grid API Map
7. WIRELESS GRID INFORMATION ELEMENT (WGIE)
Due to the processing nature of wireless grids for the IoT architecture (see Figure 8), a standard
process for authentication needs to be defined that provides for a network-wide cryptographic
challenge and response mechanism. This standard should provide for the ability to uniquely
authenticate ICD‟s to legitimate mobile access points. In order to provide authentication for the
ICD‟s in the IoT, the system must use standard cryptographic algorithms/ciphers for wireless and
RFID systems (e.g. WPA2, Simon and Speck, AES, Skipjack, etc.) and the establishment of an
information element known only to the service provider from the RSP. This information element
is referred to as the „Wireless Grid Information Element [WGIE]‟, should be programmed into all
mobile access points and known to the network infrastructure for the FMEC/IoT network.
11. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
11
Figure 8. IoT Architecture
(Source: Eichhorn 2010)
The WGIE, as displayed in Figure 9, is a 256-bit cryptographic key variable stored in the semi-
permanent memory of the mobile access point and is known to the wireless base register
authentication center (WBRAC) of the IoT system.
Figure 9. WGIE
The WBRAC provides identification, authentication and encryption for ICD‟s, provides a central
location for supporting mobile access points and is the repository for all subscriber information
12. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
12
As a secured database that stores essential encrypted subscriber information, the WBRAC plays a
key role in the operation of the wg-IoT network as it manages the services to which an ICD has
subscribed. The WBRAC is constantly subjected to heavy load of traffic to identify service
providers/subscribers, route, handle data, and provide security for the IoT system. The WBRAC
is used to conduct the IoT network‟s primary security functions and it contains the wg-IoT
network‟s set of algorithms necessary to authenticate an ICD.
8. THE ‘WG-IOT’ AUTHENTICATION PROCESS
The wg-IoT authentication process, as displayed in Figure 11, is initiated when a mobile access
point(s) attempts to confirm the identity of an ICD. This is based on the services identified from
the Grid Core and generated in the wg-IoT system. Within the WGIE, the wg-IoT service data
(IoT_SD) is a 128-bit pattern that resides in the ICD‟s semi-permanent memory. The IoT_SD is
passed wirelessly across the air between the ICD and the mobile access point. The WGIE
includes the 64-bit mobile access point‟s ESN and the ICD_IN, which is also stored in the
WBRAC. The IoT_SD is subdivided into two 64-bit potions called the IoT_SD_1 and the
IoT_SD_2. The IoT_SD_1 supports the ICD‟s authentication procedure and the IoT_SD_2
supports privacy and message confidentiality. When the ICD sends a secure activation signal to
the wg-IoT system, the ICD uses the WGIE (i.e. IoT_SD field, ESN, ICD_IN) to begin the
generation procedure for the security component (SC) authentication key [SC_auth-K] (e.g. the
SC_auth-K is a 128-bit long sequence that is stored in the ICD permanent security identification
memory). This information is used to execute the authenticate-signature procedure from the Grid
Core‟s RSP, which will yield a 128-bit numerical value for AAC.
The ACC component handles the authentication of the ICD and the authorization of resources; in
effect, the AAC provides the protocols to identify the ICD and understands that ICD‟s
relationship to a resource (i.e. what the ICD can or cannot do with a resource). The AAC is used
by all grid members and has an identity system that looks at all ICD‟s and allows policies to be
made regarding the ICD‟s grid profile. The ICD then combines the AAC with two more
numerical values from the Grid Core, the messaging and presence component [MPC] and the
resource management component [RMC].
13. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
13
Figure 10. wg-IoT Authentication
The MPC is a scalable messaging and presence protocol that manages the availability of an ICD
and the method or language of communication with that resource. The RMC is responsible for
aggregating and searching metadata about resources within the context of authentication and
works closely with the AAC and MPC. The RMC has a scheduler to manage and coordinate
resources, such as network access, and allows for ICD„s to be identified as being available. The
MPC and the RMC are filled in from values already residing in the ICD‟s memory. The MPC is a
128-bit long value that was received by the thing/object during its last access parameter message
transmitted by the network over the wg-IoT communication channel. The MPC is periodically
generated and issued by the wg-IoT system and it‟s transmitted by the network to all mobile
wireless base stations. The ICD stores and uses the most recent version of the MPC that it has in
its authentication attempts. The RMC is a 128-count field stored in the ICD and updated
whenever a parameter update order is received from the wg-IoT network on the wg-IoT secure
traffic channel. After the ICD has assembled the AAC-MPC-RMC number, called the global
unique identifier (GUID), it sends it to the mobile access point. The mobile access point
compares the information it received from the ICD with its stored value for the AAC and MPC,
along with its RMC derived from a stored service. If valid, the ICD is authenticated. If any of the
comparison fails, the mobile access point initiates a unique challenged response process or starts
an update value process.
In the update value process (see Figure 12), the wg-IoT system responds by calculating new
authentication values and challenging the ICD. First, the WBRAC in the wg-IoT system sends an
update message to the mobile access point telling it that the ICD is to be updated and it passes a
value to the mobile access point. This random number that the WBRAC has used, together with
the ICD to calculate the new value. Since the WGIE is stored in both the ICD and in the
WBRAC, the mobile access point sends the value to the ICD in an update order over the wg-IoT
secure traffic channel. When the update order arrives at the ICD, it causes the unit to execute an
IoT_SD generation procedure. In this procedure, the ICD uses the AAC, ESN and the SC_auth-K
14. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
14
to produce an IoT_SD_New value. Meanwhile, the WBRAC has also used the AAC and
SC_auth-K to generate its version of the IoT_SD_New value. Next, the ICD generates a random,
256-bit long number called the “thing-object mobile access point (TO_MAP)”. The TO_MAP
number is used to challenge the mobile access point. The mobile access point issues the challenge
via a mobile access challenge order message that is transmitted via the wg-IoT secure traffic
channel. The ICD continues on by running an authorization-signature procedure using its
IOT_SD_New and the TO_MAP (coupled with the ESN and ICD_IN). The result is a new
number called the AUTH_SIGN_MAP within the wireless grid security component.
Figure 11. Update Value for AUTH_SIGN_MAP
At the same time that the ICD is calculating the AUTH_SIGN_MAP, the mobile access point
received the TO_MAP from the ICD and has started its own authorization-signature procedure.
The mobile access point forwards the challenge order to the WBRAC and sends an
acknowledgement on receipt of the order to the ICD. The SC uses the TO_MAP (calculated by
the ICD) and the IOT_SD_New (calculated by the WBRAC) to generate its own version of the
AUTH_SIGN_MAP. The SC then sends its AUTH_SIGN_MAP to the mobile access point in a
mobile access point challenge response message. The mobile access point sends this response to
the ICD via a mobile access point challenge response order message via the wg-IoT secure traffic
channel. The mobile access point challenge confirmation order must be received by the ICD
within a timer period of 1s after it has received acknowledgement of reception of the challenge
order. If it does not receive the confirmation order within the specific time, the ICD will discard
the AUTH_SIGN_MAP and terminate the update value process.
Once the ICD has both copies of the AUTH_SIGN_MAP in its possession, it conducts a
comparison of the two. If the comparison results in a successful match, the ICD resets the
original IOT_SD_New, replacing them with the new values of the IOT_SD_1New and the
IOT_SD_2New. If the comparison results in an unsuccessful match, the ICD discards the
IOT_SD_1New and the IOT_SD_2New values and sends an update rejection message to the
mobile access point; thus denying the wg-IoT system access and causing the authentication
procedure to begin again. With a successful match and reset, the ICD sends an update
confirmation message to the mobile access point. After it has received this message, the mobile
access point resets its IOT_SD_1 and the IOT_SD_New value using the IOT_SD_1 New and the
IOT_SD_2 New values it received from the WBRAC. The ICD has now been authenticated and
proceeds to the authorization and encryption process (see Figure 13).
15. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
15
If any of the calculated values fails a comparison made by the mobile access point during an
authentication procedure, then the mobile access point may deem the attempt unsuccessful. It can
then terminate the current authentication procedure and initiate the unique challenge response
process. This process can be carried out on the wg-IoT secure traffic channels since the mobile
access point generates a 64-bit long value called the WMAP and send it to the ICD via the
authentication challenge message. This message is sent on the wg-IoT secure traffic channel.
When the ICD receives this message, it performs an authorization-signature calculation. Its takes
the value and makes it the 64 most significant bits of the WMAP. It also takes the 16 least
significant bits of the WBRAC and makes those the 16 least significant bits of the WMAP. The
ICD then calculates the authorization-signature, which is used to fill the AUTH_SIGN_MAP
field.
The AUTH_SIGN_MAP is then sent to the mobile access point. The mobile access point then
compares the ICD AUTH_SIGN_MAP with its own version of the AUTH_SIGN_MAP. If the
two do not match, the mobile access point will drop the attempt, deny any further attempt to
access the wg-IoT network by the ICD or initiate an update process. If authentication is
successful, the mobile access point can move on to authorization and message encryption, which
involves scrambling the data signal stream within the wg-IoT network as displayed in Figure 13.
Figure 12. Validating the AUTH_SIGN_MAP
9. CONCLUSION
Unlike wired networks, wireless grids and FMECs are not limited by physical space. This
potentially opens up the network to attack from rogue ICDs and users who may spy on the
wireless transmission or gain unauthorized access to the network from the inside or outside.
Traditional thieves, hackers, high-tech criminals, government sponsored organizations, viruses,
and other types of malicious code will continue to be causes for security concerns on these
networks. The information passed on these networks is exposed to malicious attempts to obtain
the information without proper authorization. These new systems must be designed to minimize
the vulnerabilities of the networks and the information contained within them. However, as
vulnerable as wired networks are for potential attacks, these networks are even more vulnerable.
16. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
16
The intent of this article is to hypothesize a generic authentication methodology for wireless
grid/FMECs use for the IoT architecture. The proposed methodology, called wg-IoT, includes the
integration of fog computing, wireless grids and FMECs to create this new IoT architecture and
must be further researched. The authentication process developed from the wireless grid RSP still
has to be developed and proposed for modeling the authentication of ICD‟s, which allows
strategies and approaches for enhancing the information security architecture for further
development. There are numerous complex considerations, which must be taken into account
when implementing this process, and without adequate forethought, these new ICDs and FMECs
may be ill advised.
REFERENCES
[1] Agarwal, A., Norman, D. and Gupta, A. (2004). Wireless grids: approaches, architectures and
technical challenges (Report No. 4459-04). Cambridge, MA: Massachusetts Institute of Technology
(MIT).
[2] Ahmed, M., & Litchfield, A. T. (2018). Taxonomy for identification of security issues in cloud
computing environments. Journal of Computer Information Systems, 58(1), 79-88.
[3] Alharbi, S., Rodriguez, P., Maharaja, R., Iyer, P., Subaschandrabose, N., and Ye, Z. "Secure the
internet of things with challenge response authentication in fog computing," 2017 IEEE 36th
International Performance Computing and Communications Conference (IPCCC), San Diego, CA,
2017, pp. 1-2. doi: 10.1109/PCCC.2017.8280489.
[4] Amor, A.B., Abid, M., and Meddeb, A. "A Privacy-Preserving Authentication Scheme in an Edge-
Fog Environment," 2017 IEEE/ACS 14th International Conference on Computer Systems and
Applications (AICCSA), Hammamet, Tunisia, 2017, pp. 1225-1231. doi: 10.1109/AICCSA.2017.57
[5] Bonomi, F., Milito, R., Zhu, J., & Addepalli, S. (2012, August). Fog computing and its role in the
internet of things. In Proceedings of the first edition of the MCC workshop on Mobile cloud
computing (pp. 13-16). ACM.
[6] Brooks, T. T. (Ed.). (2017). Cyber-assurance for the Internet of Things. John Wiley & Sons.
[7] Brooks, T., Kaarst-Brown, M., Caicedo, C., Park, J., & McKnight, L. (2013, December). A failure to
communicate: security vulnerabilities in the gridstreamx edgeware application. In Internet
Technology and Secured Transactions (ICITST), 2013 8th International Conference for (pp. 516-
523). IEEE.
[8] Brooks, T and McKnight, L. (2017). "A Steady‐ State Framework for Assessing Security
Mechanisms in a Cloud‐ of‐ Things Architecture." In Cyber‐ Assurance for the Internet of Things:
pp. 225-247.
[9] Cisco Fog Computing Solutions (2015a). Unleash the power of the Internet of Things. Cisco Systems
Inc. (2015). Available on: https://www.cisco.com/c/dam/en_us/solutions/trends/iot/docs/computing-
solutions.pdf.
[10] Cisco Fog Computing (2015b). The Internet of Things: Extend the Cloud to Where the Things Are.
Available on: http://www. cisco. com/c/dam/en_us/solutions/trends/iot/docs/computingoverview. pdf.
[11] Covington, M.J. and Carskadden, R., (2013). "Threat implications of the Internet of Things," Cyber
Conflict (CyCon), 2013 5th International Conference on , vol., no., pp.1,12, 4-7 June 2013.
[12] Eichhorn, J. (2010, November). GREENER, SAFER, SMARTER Considerations in Building a Smart
Grid Communications Network, TROPOS Network. Presentation retrieved on March 23, 2018 from
http://slideplayer.com/slide/5850758/.
[13] Ekanayake, B. N., Halgamuge, M. N., & Syed, A. (2018). Security and Privacy Issues of Fog
Computing for the Internet of Things (IoT). In Cognitive Computing for Big Data Systems Over IoT
(pp. 139-174). Springer, Cham.
[14] Firdous, S., Baig, Z., Valli, C., and Ibrahim, A. "Modelling and Evaluation of Malicious Attacks
against the IoT MQTT Protocol," 2017 IEEE International Conference on Internet of Things
(iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical
and Social Computing (CPSCom) and IEEE Smart Data (SmartData), Exeter, 2017, pp. 748-755.
[15] Gupta, S., & Gupta, B. B. (2018). XSS-secure as a service for the platforms of online social network-
based multimedia web applications in cloud. Multimedia Tools and Applications, 77(4), 4829-4861.
17. International Journal of Ubiquitous Computing (IJU), Vol.13, No.1/2, April 2022
17
[16] Iorga, M., Feldman, L., Barton, R., Martin, M. J., Goren, N. S., & Mahmoudi, C. (2018). Fog
Computing Conceptual Model (NIST Special Publication 500-325). National Institute of Standards
and Technology. Retrieved March 22, 2018, from https://doi.org/10.6028/NIST.SP.500-325.
[17] Li, X., Liang, X., Lu, R., Shen, X., Lin, X., and Zhu, H. (2012). Securing smart grid: cyber-attacks,
countermeasures, and challenges. Communications Magazine, IEEE, 50(8), 38-45.
[18] McKinley, P. K., Samimi, F. A., Shapiro, J. K., and Tang, C. (2006). Service Clouds: a distributed
infrastructure for constructing autonomic communication services, Proc. of the 2nd IEEE
International Symposium on Dependable, Autonomic and Secure Computing, IEEE, pp. 341-348.
[19] McKnight, L. W., Howison, J. and Bradner, S. (2004) „Guest editors' introduction: Wireless grids--
distributed resource sharing by mobile, nomadic, and fixed devices‟, IEEE Internet Computing, Vol.
8, No. 4, pp. 24-31.
[20] McKnight, L., Marsden, J., Treglia, J., Nanno, E., Hameed, A. and Lu, Y. (2015). Open specifications
for wireless grids technical requirements, version 0.3. In L. McKnight (Ed.), (Syracuse University)
pp. 1-45.
[21] Mukherjee, M., Matam, R., Shu, L., Maglaras, L., Ferrag, M. A., Choudhury, N., & Kumar, V.
(2017). Security and privacy in fog computing: Challenges. IEEE Access, 5, 19293-19304.
[22] Samimi, F. A., McKinley, P. K., and Sadjadi, S. M. (2006). Mobile service clouds: A self-managing
infrastructure for autonomic mobile computing services. In Self-Managed Networks, Systems, and
Services (pp. 130-141). Springer Berlin Heidelberg.
[23] Sheu, J. P., Chen, P. C., & Hsu, C. S. (2008). A distributed localization scheme for wireless sensor
networks with improved grid-scan and vector-based refinement. IEEE transactions on mobile
computing, 7(9), 1110-1123.
[24] Uckelmann, D., Harrison, M., & Michahelles, F. (2011). An architectural approach towards the future
internet of things. In Architecting the internet of things (pp. 1-24). Springer, Berlin, Heidelberg.
[25] Vermesan, O., Friess, P., Guillemin, P., Gusmeroli, S., Sundmaeker, H., Bassi, A., and Doody, P.
(2011). Internet of things strategic research roadmap. Internet of Things-Global Technological and
Societal Trends, 9-52.
[26] Yan, X., Şekercioğlu, Y. A., & Narayanan, S. (2010). A survey of vertical handover decision
algorithms in Fourth Generation heterogeneous wireless networks. Computer networks, 54(11), 1848-
1863.
[27] Yi, S., Qin, Z., & Li, Q. (2015, August). Security and privacy issues of fog computing: A survey. In
International Conference on Wireless Algorithms, Systems, and Applications (pp. 685-695). Springer,
Cham.
[28] Yi, S., Li, C., & Li, Q. (2015, June). A survey of fog computing: concepts, applications and issues. In
Proceedings of the 2015 Workshop on Mobile Big Data (pp. 37-42). ACM.
[29] Zeng, W. Y., Zhao, Y. L., Zeng, J. W., & Song, W. (2008, October). Mobile grid architecture design
and application. In Wireless Communications, Networking and Mobile Computing, 2008.
WiCOM'08. 4th International Conference on (pp. 1-4). IEEE.
[30] Zhang, Y., Yu, R., Nekovee, M., Liu, Y., Xie, S., and Gjessing, S. (2012). Cognitive machine-to-
machine communications: visions and potentials for the smart grid. Network, IEEE, 26(3), 6-13.
[31] Zhu, J., Chan, D. S., Prabhu, M. S., Natarajan, P., Hu, H., & Bonomi, F. (2013, March). Improving
web sites performance using edge servers in fog computing architecture. In Service Oriented System
Engineering (SOSE), 2013 IEEE 7th International Symposium on (pp. 320-323). IEEE.