Rapid expansion of wireless sensor network-internet of things (WSN-IoT) in terms of application and technologies has led to wide research considering efficiency and security aspects. Considering the efficiency approach such as data aggregation along with consensus mechanism has been one of the efficient and secure approaches, however, privacy has been one of major concern and it remains an open issue due to low classification and high misclassification rate. This research work presents the privacy and reliable aware discrete (PRD-aggregation) framework to protect and secure the privacy of the node. It works by initializing the particular variable for each node and defining the threshold; further nodes update their state through the functions, and later consensus is developed among the sensor nodes, which further updates. The novelty of PRD is discretized transmission for efficiency and security. PRD-aggregation offers reliability through efficient termination criteria and avoidance of transmission failure. PRD-aggregation framework is evaluated considering the number of deceptive nodes for securing the node in the network. Furthermore, comparative analysis proves the marginal improvisation in terms of discussed parameter against the existing protocol.
A signature-based data security and authentication framework for internet of...IJECEIAES
Internet of things (IoT) is the next big revolution in modernized network technologies connecting a massive number of heterogeneous smart appliances and physical objects. Owing to these technologies' novelty, various issues are characterized by security concerns are the most prioritized issue. A review of existing security approaches highlights that they are very particular about the solution towards a specific attack and cannot resist any unknown attacker. Therefore, this manuscript presents a novel computational model that introduces a unique authentication process using a simplified encryption strategy. The simulated study outcome shows that the proposed system offers efficient security and efficient data transmission performance in the presence of an unknown adversary. Hence, the study outcome exhibits better effects than frequently used security solutions when implemented in a vulnerable IoT environment.
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.
Cybersecurity stands as the bedrock of our digital world, safeguarding systems, networks, and data from a rising tide of cyber threats. In the era of the Internet of Things (IoT), wherean ever-expanding array of devices and objects are seamlessly interconnected, the importance of cybersecurity has escalated to unprecedented levels.
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.
A signature-based data security and authentication framework for internet of...IJECEIAES
Internet of things (IoT) is the next big revolution in modernized network technologies connecting a massive number of heterogeneous smart appliances and physical objects. Owing to these technologies' novelty, various issues are characterized by security concerns are the most prioritized issue. A review of existing security approaches highlights that they are very particular about the solution towards a specific attack and cannot resist any unknown attacker. Therefore, this manuscript presents a novel computational model that introduces a unique authentication process using a simplified encryption strategy. The simulated study outcome shows that the proposed system offers efficient security and efficient data transmission performance in the presence of an unknown adversary. Hence, the study outcome exhibits better effects than frequently used security solutions when implemented in a vulnerable IoT environment.
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.
Cybersecurity stands as the bedrock of our digital world, safeguarding systems, networks, and data from a rising tide of cyber threats. In the era of the Internet of Things (IoT), wherean ever-expanding array of devices and objects are seamlessly interconnected, the importance of cybersecurity has escalated to unprecedented levels.
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.
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.
SECURITY AND PRIVACY AWARE PROGRAMMING MODEL FOR IOT APPLICATIONS IN CLOUD EN...ijccsa
The introduction of Internet of Things (IoT) applications into daily life has raised serious privacy concerns
among consumers, network service providers, device manufacturers, and other parties involved. This paper
gives a high-level overview of the three phases of data collecting, transmission, and storage in IoT systems
as well as current privacy-preserving technologies. The following elements were investigated during these
three phases:(1) Physical and data connection layer security mechanisms(2) Network remedies(3)
Techniques for distributing and storing data. Real-world systems frequently have multiple phases and
incorporate a variety of methods to guarantee privacy. Therefore, for IoT research, design, development,
and operation, having a thorough understanding of all phases and their technologies can be beneficial. In
this Study introduced two independent methodologies namely generic differential privacy (GenDP) and
Cluster-Based Differential privacy ( Cluster-based DP) algorithms for handling metadata as intents and
intent scope to maintain privacy and security of IoT data in cloud environments. With its help, we can
virtual and connect enormous numbers of devices, get a clearer understanding of the IoT architecture, and
store data eternally. However, due of the dynamic nature of the environment, the diversity of devices, the
ad hoc requirements of multiple stakeholders, and hardware or network failures, it is a very challenging
task to create security-, privacy-, safety-, and quality-aware Internet of Things apps. It is becoming more
and more important to improve data privacy and security through appropriate data acquisition. The
proposed approach resulted in reduced loss performance as compared to Support Vector Machine (SVM) ,
Random Forest (RF) .
A review on machine learning based intrusion detection system for internet of...IJECEIAES
Within an internet of things (IoT) environment, the fundamental purpose of various devices is to gather the abundant amount of data that is being generated and then transmit this data to the predetermined server over the internet. IoT connects billions of objects and the internet to communicate without human intervention. But network security and privacy issues are increasing very fast, in today's world. Because of the prevalence of technological advancement in regular activities, internet security has evolved into a necessary requirement. Because technology is integrated into every aspect of contemporary life, cyberattacks on the internet of things represent a bigger danger than attacks against traditional networks. Researchers have found that combining machine learning techniques into an intrusion detection system (IDS) is an efficient way to get beyond the limitations of conventional IDSs in an IoT context. This research presents a comprehensive literature assessment and develops an intrusion detection system that makes use of machine learning techniques to address security problems in an IoT environment. Along with a comprehensive look at the state of the art in terms of intrusion detection systems for IoT-enabled environments, this study also examines the attributes of approaches, common datasets, and existing methods utilized to construct such systems.
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.
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.
Unlocking the Potential: A Comprehensive Guide to Understanding and Securing ...cyberprosocial
The Internet of Things, or IoT, has become a disruptive force in the era of connected devices, changing the way we interact with our surroundings. In the center of this networked web is an essential element called IoT gateways. The purpose of this paper is to offer a thorough overview of IoT gateways, their importance in enabling smooth device connectivity, and the critical necessity to safeguard these gateways against growing cyber threats.
CAN BLOCKCHAIN BE A SOLUTION TO IOT TECHNICAL AND SECURITY ISSUESIJNSA Journal
The Internet of Things (IoT) is a growing trend in technology that interconnects millions of physical devices from any location anytime. Currently, IoT devices have become an integral part of human lives, as such organizations are deeply concerned with its security and technical issues. Blockchain system comprises a distributed digital ledger which is shared among community of users on the Internet; validated and recorded transactions in the ledger which cannot be altered or removed. We presented the challenges of IoT devices and how blockchain can be used to alleviate these problems. An outline of how to integrate blockchain with IoT was tackled, highlighting the challenges of IoT and how blockchain can remedy the issues. It was concluded that blockchain has the capability to curb the challenges posed by IoT devices.
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
Comprehensive Survey on Security Problems and Key Technologies of the Interne...RSIS International
Internet of things (IoT) is a collection of many
interconnected objects, services, humans, and devices that can
communicate, share data, and information to achieve a common
goal in different areas and applications. The vision of IoT is to
enable devices to collaborate with each other on the Internet. IoT
security focuses on authentication and access control protocols.
IoT security is the area with protection connected devices and
networks. There are many key challenges in designing a secure
IoT: Privacy, Authentication, Access Control, Trust,
Confidentiality, Mobile Security, etc. Attacks on IoT security
devices are physical attacks, side channel attacks, cryptanalysis
attacks, software attacks, network attacks. This paper describes
Security Problems of IoT, Security issues and Key Technologies
of IoT.
Comprehensive survey on security problems and key technologies of the interne...RSIS International
Internet of things (IoT) is a collection of many
interconnected objects, services, humans, and devices that can
communicate, share data, and information to achieve a common
goal in different areas and applications. The vision of IoT is to
enable devices to collaborate with each other on the Internet. IoT
security focuses on authentication and access control protocols.
IoT security is the area with protection connected devices and
networks. There are many key challenges in designing a secure
IoT: Privacy, Authentication, Access Control, Trust,
Confidentiality, Mobile Security, etc. Attacks on IoT security
devices are physical attacks, side channel attacks, cryptanalysis
attacks, software attacks, network attacks. This paper describes
Security Problems of IoT, Security issues and Key Technologies
of IoT.
A survey on Internet of Things (IoT) security : Challenges and Current statusvivatechijri
When Internet of Things (IoT) applications become a part of people’s daily life, security issues in IoT have caught substantial attention in both academia and industry. Compared to traditional computing systems, IoT systems have more inherent vulnerabilities, and in the intervening time, could have higher security requirements. However, the current design of IoT does not successfully address the higher security requirements postured by those vulnerabilities. Many recent attacks on IoT systems have shown that novel security solutions are needed to defend this emerging system. This paper purposes to examine security challenges resulted from the special characteristics of the IoT systems and the new features of the IoT applications. This could help pave the road to better security solution design. Furthermore, three architectural security designs are suggested and analyzed. Examples of how to implement these designs are discussed. Finally, for each layer in IoT architecture, open issues are also identified.
Malware threat analysis techniques and approaches for IoT applications: a reviewjournalBEEI
Internet of things (IoT) is a concept that has been widely used to improve business efficiency and customer’s experience. It involves resource constrained devices connecting to each other with a capability of sending data, and some with receiving data at the same time. The IoT environment enhances user experience by giving room to a large number of smart devices to connect and share information. However, with the sophistication of technology has resulted in IoT applications facing with malware threat. Therefore, it becomes highly imperative to give an understanding of existing state-of-the-art techniques developed to address malware threat in IoT applications. In this paper, we studied extensively the adoption of static, dynamic and hybrid malware analyses in proffering solution to the security problems plaguing different IoT applications. The success of the reviewed analysis techniques were observed through case studies from smart homes, smart factories, smart gadgets and IoT application protocols. This study gives a better understanding of the holistic approaches to malware threats in IoT applications and the way forward for strengthening the protection defense in IoT applications.
Internet of Things IoT Anytime Anywhere Anything ConnectivityYogeshIJTSRD
This paper presents the key challenges in the domain of IoT. The key challenges associated with the development of IoT, industry as well as government, Industrial IoT systems, the related security and privacy challenges has been reviewed and presented. Vulnerability of Internet of Things systems have been improved with the advent of new computational systems for IoT. However, the current design of IoT does not effectively address the higher security requirements posed by those vulnerabilities. Many recent attacks on IoT systems have shown that novel security solutions are needed to protect this emerging system. Nidhi Chadha | Ramandeep Kaur "Internet of Things (IoT): Anytime-Anywhere-Anything Connectivity" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd40008.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-network/40008/internet-of-things-iot-anytimeanywhereanything-connectivity/nidhi-chadha
Architectural Layers of Internet of Things: Analysis of Security Threats and ...Scientific Review SR
A pervasive network architecture that interconnect heterogeneous objects, devices, technologies and services called
Internet of Things has prompted a drastic change in demand of smart devices which in turn has increased the rate of
data exchange. These smart devices are built with numerous sensors which collect information from other interacting
devices, process it and send it to remote locations for storage or further processing. Although this mechanism of data
processing and sharing has contributed immensely to the information world, it has recently posed high security risk
on privacy and data confidentiality. This paper therefore analyses different security threats to data at different
architectural layers of Internet of Things, possible countermeasures and other in-depth security measures for Internet
of Things. The paper identifies device authentication on IoT network to be of paramount impo rtance in securing IoT
systems. This paper also suggests some essential technologies of security such as encryption for securing IoT
devices and the data shared over IoT network
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
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.
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
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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.
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among consumers, network service providers, device manufacturers, and other parties involved. This paper
gives a high-level overview of the three phases of data collecting, transmission, and storage in IoT systems
as well as current privacy-preserving technologies. The following elements were investigated during these
three phases:(1) Physical and data connection layer security mechanisms(2) Network remedies(3)
Techniques for distributing and storing data. Real-world systems frequently have multiple phases and
incorporate a variety of methods to guarantee privacy. Therefore, for IoT research, design, development,
and operation, having a thorough understanding of all phases and their technologies can be beneficial. In
this Study introduced two independent methodologies namely generic differential privacy (GenDP) and
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intent scope to maintain privacy and security of IoT data in cloud environments. With its help, we can
virtual and connect enormous numbers of devices, get a clearer understanding of the IoT architecture, and
store data eternally. However, due of the dynamic nature of the environment, the diversity of devices, the
ad hoc requirements of multiple stakeholders, and hardware or network failures, it is a very challenging
task to create security-, privacy-, safety-, and quality-aware Internet of Things apps. It is becoming more
and more important to improve data privacy and security through appropriate data acquisition. The
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Within an internet of things (IoT) environment, the fundamental purpose of various devices is to gather the abundant amount of data that is being generated and then transmit this data to the predetermined server over the internet. IoT connects billions of objects and the internet to communicate without human intervention. But network security and privacy issues are increasing very fast, in today's world. Because of the prevalence of technological advancement in regular activities, internet security has evolved into a necessary requirement. Because technology is integrated into every aspect of contemporary life, cyberattacks on the internet of things represent a bigger danger than attacks against traditional networks. Researchers have found that combining machine learning techniques into an intrusion detection system (IDS) is an efficient way to get beyond the limitations of conventional IDSs in an IoT context. This research presents a comprehensive literature assessment and develops an intrusion detection system that makes use of machine learning techniques to address security problems in an IoT environment. Along with a comprehensive look at the state of the art in terms of intrusion detection systems for IoT-enabled environments, this study also examines the attributes of approaches, common datasets, and existing methods utilized to construct such systems.
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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.
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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.
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‘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.
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The Internet of Things, or IoT, has become a disruptive force in the era of connected devices, changing the way we interact with our surroundings. In the center of this networked web is an essential element called IoT gateways. The purpose of this paper is to offer a thorough overview of IoT gateways, their importance in enabling smooth device connectivity, and the critical necessity to safeguard these gateways against growing cyber threats.
CAN BLOCKCHAIN BE A SOLUTION TO IOT TECHNICAL AND SECURITY ISSUESIJNSA Journal
The Internet of Things (IoT) is a growing trend in technology that interconnects millions of physical devices from any location anytime. Currently, IoT devices have become an integral part of human lives, as such organizations are deeply concerned with its security and technical issues. Blockchain system comprises a distributed digital ledger which is shared among community of users on the Internet; validated and recorded transactions in the ledger which cannot be altered or removed. We presented the challenges of IoT devices and how blockchain can be used to alleviate these problems. An outline of how to integrate blockchain with IoT was tackled, highlighting the challenges of IoT and how blockchain can remedy the issues. It was concluded that blockchain has the capability to curb the challenges posed by IoT devices.
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
Comprehensive Survey on Security Problems and Key Technologies of the Interne...RSIS International
Internet of things (IoT) is a collection of many
interconnected objects, services, humans, and devices that can
communicate, share data, and information to achieve a common
goal in different areas and applications. The vision of IoT is to
enable devices to collaborate with each other on the Internet. IoT
security focuses on authentication and access control protocols.
IoT security is the area with protection connected devices and
networks. There are many key challenges in designing a secure
IoT: Privacy, Authentication, Access Control, Trust,
Confidentiality, Mobile Security, etc. Attacks on IoT security
devices are physical attacks, side channel attacks, cryptanalysis
attacks, software attacks, network attacks. This paper describes
Security Problems of IoT, Security issues and Key Technologies
of IoT.
Comprehensive survey on security problems and key technologies of the interne...RSIS International
Internet of things (IoT) is a collection of many
interconnected objects, services, humans, and devices that can
communicate, share data, and information to achieve a common
goal in different areas and applications. The vision of IoT is to
enable devices to collaborate with each other on the Internet. IoT
security focuses on authentication and access control protocols.
IoT security is the area with protection connected devices and
networks. There are many key challenges in designing a secure
IoT: Privacy, Authentication, Access Control, Trust,
Confidentiality, Mobile Security, etc. Attacks on IoT security
devices are physical attacks, side channel attacks, cryptanalysis
attacks, software attacks, network attacks. This paper describes
Security Problems of IoT, Security issues and Key Technologies
of IoT.
A survey on Internet of Things (IoT) security : Challenges and Current statusvivatechijri
When Internet of Things (IoT) applications become a part of people’s daily life, security issues in IoT have caught substantial attention in both academia and industry. Compared to traditional computing systems, IoT systems have more inherent vulnerabilities, and in the intervening time, could have higher security requirements. However, the current design of IoT does not successfully address the higher security requirements postured by those vulnerabilities. Many recent attacks on IoT systems have shown that novel security solutions are needed to defend this emerging system. This paper purposes to examine security challenges resulted from the special characteristics of the IoT systems and the new features of the IoT applications. This could help pave the road to better security solution design. Furthermore, three architectural security designs are suggested and analyzed. Examples of how to implement these designs are discussed. Finally, for each layer in IoT architecture, open issues are also identified.
Malware threat analysis techniques and approaches for IoT applications: a reviewjournalBEEI
Internet of things (IoT) is a concept that has been widely used to improve business efficiency and customer’s experience. It involves resource constrained devices connecting to each other with a capability of sending data, and some with receiving data at the same time. The IoT environment enhances user experience by giving room to a large number of smart devices to connect and share information. However, with the sophistication of technology has resulted in IoT applications facing with malware threat. Therefore, it becomes highly imperative to give an understanding of existing state-of-the-art techniques developed to address malware threat in IoT applications. In this paper, we studied extensively the adoption of static, dynamic and hybrid malware analyses in proffering solution to the security problems plaguing different IoT applications. The success of the reviewed analysis techniques were observed through case studies from smart homes, smart factories, smart gadgets and IoT application protocols. This study gives a better understanding of the holistic approaches to malware threats in IoT applications and the way forward for strengthening the protection defense in IoT applications.
Internet of Things IoT Anytime Anywhere Anything ConnectivityYogeshIJTSRD
This paper presents the key challenges in the domain of IoT. The key challenges associated with the development of IoT, industry as well as government, Industrial IoT systems, the related security and privacy challenges has been reviewed and presented. Vulnerability of Internet of Things systems have been improved with the advent of new computational systems for IoT. However, the current design of IoT does not effectively address the higher security requirements posed by those vulnerabilities. Many recent attacks on IoT systems have shown that novel security solutions are needed to protect this emerging system. Nidhi Chadha | Ramandeep Kaur "Internet of Things (IoT): Anytime-Anywhere-Anything Connectivity" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-5 | Issue-3 , April 2021, URL: https://www.ijtsrd.com/papers/ijtsrd40008.pdf Paper URL: https://www.ijtsrd.com/computer-science/computer-network/40008/internet-of-things-iot-anytimeanywhereanything-connectivity/nidhi-chadha
Architectural Layers of Internet of Things: Analysis of Security Threats and ...Scientific Review SR
A pervasive network architecture that interconnect heterogeneous objects, devices, technologies and services called
Internet of Things has prompted a drastic change in demand of smart devices which in turn has increased the rate of
data exchange. These smart devices are built with numerous sensors which collect information from other interacting
devices, process it and send it to remote locations for storage or further processing. Although this mechanism of data
processing and sharing has contributed immensely to the information world, it has recently posed high security risk
on privacy and data confidentiality. This paper therefore analyses different security threats to data at different
architectural layers of Internet of Things, possible countermeasures and other in-depth security measures for Internet
of Things. The paper identifies device authentication on IoT network to be of paramount impo rtance in securing IoT
systems. This paper also suggests some essential technologies of security such as encryption for securing IoT
devices and the data shared over IoT network
A trust based secure access control using authentication mechanism for intero...IJECEIAES
The internet of things (IoT) is a revolutionary innovation in many aspects of our society including interactions, financial activity, and global security such as the military and battlefield internet. Due to the limited energy and processing capacity of network devices, security, energy consumption, compatibility, and device heterogeneity are the long-term IoT problems. As a result, energy and security are critical for data transmission across edge and IoT networks. Existing IoT interoperability techniques need more computation time, have unreliable authentication mechanisms that break easily, lose data easily, and have low confidentiality. In this paper, a key agreement protocol-based authentication mechanism for IoT devices is offered as a solution to this issue. This system makes use of information exchange, which must be secured to prevent access by unauthorized users. Using a compact contiki/cooja simulator, the performance and design of the suggested framework are validated. The simulation findings are evaluated based on detection of malicious nodes after 60 minutes of simulation. The suggested trust method, which is based on privacy access control, reduced packet loss ratio to 0.32%, consumed 0.39% power, and had the greatest average residual energy of 0.99 mJoules at 10 nodes.
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.
Bibliometric analysis highlighting the role of women in addressing climate ch...IJECEIAES
Fossil fuel consumption increased quickly, contributing to climate change
that is evident in unusual flooding and draughts, and global warming. Over
the past ten years, women's involvement in society has grown dramatically,
and they succeeded in playing a noticeable role in reducing climate change.
A bibliometric analysis of data from the last ten years has been carried out to
examine the role of women in addressing the climate change. The analysis's
findings discussed the relevant to the sustainable development goals (SDGs),
particularly SDG 7 and SDG 13. The results considered contributions made
by women in the various sectors while taking geographic dispersion into
account. The bibliometric analysis delves into topics including women's
leadership in environmental groups, their involvement in policymaking, their
contributions to sustainable development projects, and the influence of
gender diversity on attempts to mitigate climate change. This study's results
highlight how women have influenced policies and actions related to climate
change, point out areas of research deficiency and recommendations on how
to increase role of the women in addressing the climate change and
achieving sustainability. To achieve more successful results, this initiative
aims to highlight the significance of gender equality and encourage
inclusivity in climate change decision-making processes.
Voltage and frequency control of microgrid in presence of micro-turbine inter...IJECEIAES
The active and reactive load changes have a significant impact on voltage
and frequency. In this paper, in order to stabilize the microgrid (MG) against
load variations in islanding mode, the active and reactive power of all
distributed generators (DGs), including energy storage (battery), diesel
generator, and micro-turbine, are controlled. The micro-turbine generator is
connected to MG through a three-phase to three-phase matrix converter, and
the droop control method is applied for controlling the voltage and
frequency of MG. In addition, a method is introduced for voltage and
frequency control of micro-turbines in the transition state from gridconnected mode to islanding mode. A novel switching strategy of the matrix
converter is used for converting the high-frequency output voltage of the
micro-turbine to the grid-side frequency of the utility system. Moreover,
using the switching strategy, the low-order harmonics in the output current
and voltage are not produced, and consequently, the size of the output filter
would be reduced. In fact, the suggested control strategy is load-independent
and has no frequency conversion restrictions. The proposed approach for
voltage and frequency regulation demonstrates exceptional performance and
favorable response across various load alteration scenarios. The suggested
strategy is examined in several scenarios in the MG test systems, and the
simulation results are addressed.
Enhancing battery system identification: nonlinear autoregressive modeling fo...IJECEIAES
Precisely characterizing Li-ion batteries is essential for optimizing their
performance, enhancing safety, and prolonging their lifespan across various
applications, such as electric vehicles and renewable energy systems. This
article introduces an innovative nonlinear methodology for system
identification of a Li-ion battery, employing a nonlinear autoregressive with
exogenous inputs (NARX) model. The proposed approach integrates the
benefits of nonlinear modeling with the adaptability of the NARX structure,
facilitating a more comprehensive representation of the intricate
electrochemical processes within the battery. Experimental data collected
from a Li-ion battery operating under diverse scenarios are employed to
validate the effectiveness of the proposed methodology. The identified
NARX model exhibits superior accuracy in predicting the battery's behavior
compared to traditional linear models. This study underscores the
importance of accounting for nonlinearities in battery modeling, providing
insights into the intricate relationships between state-of-charge, voltage, and
current under dynamic conditions.
Smart grid deployment: from a bibliometric analysis to a surveyIJECEIAES
Smart grids are one of the last decades' innovations in electrical energy.
They bring relevant advantages compared to the traditional grid and
significant interest from the research community. Assessing the field's
evolution is essential to propose guidelines for facing new and future smart
grid challenges. In addition, knowing the main technologies involved in the
deployment of smart grids (SGs) is important to highlight possible
shortcomings that can be mitigated by developing new tools. This paper
contributes to the research trends mentioned above by focusing on two
objectives. First, a bibliometric analysis is presented to give an overview of
the current research level about smart grid deployment. Second, a survey of
the main technological approaches used for smart grid implementation and
their contributions are highlighted. To that effect, we searched the Web of
Science (WoS), and the Scopus databases. We obtained 5,663 documents
from WoS and 7,215 from Scopus on smart grid implementation or
deployment. With the extraction limitation in the Scopus database, 5,872 of
the 7,215 documents were extracted using a multi-step process. These two
datasets have been analyzed using a bibliometric tool called bibliometrix.
The main outputs are presented with some recommendations for future
research.
Use of analytical hierarchy process for selecting and prioritizing islanding ...IJECEIAES
One of the problems that are associated to power systems is islanding
condition, which must be rapidly and properly detected to prevent any
negative consequences on the system's protection, stability, and security.
This paper offers a thorough overview of several islanding detection
strategies, which are divided into two categories: classic approaches,
including local and remote approaches, and modern techniques, including
techniques based on signal processing and computational intelligence.
Additionally, each approach is compared and assessed based on several
factors, including implementation costs, non-detected zones, declining
power quality, and response times using the analytical hierarchy process
(AHP). The multi-criteria decision-making analysis shows that the overall
weight of passive methods (24.7%), active methods (7.8%), hybrid methods
(5.6%), remote methods (14.5%), signal processing-based methods (26.6%),
and computational intelligent-based methods (20.8%) based on the
comparison of all criteria together. Thus, it can be seen from the total weight
that hybrid approaches are the least suitable to be chosen, while signal
processing-based methods are the most appropriate islanding detection
method to be selected and implemented in power system with respect to the
aforementioned factors. Using Expert Choice software, the proposed
hierarchy model is studied and examined.
Enhancing of single-stage grid-connected photovoltaic system using fuzzy logi...IJECEIAES
The power generated by photovoltaic (PV) systems is influenced by
environmental factors. This variability hampers the control and utilization of
solar cells' peak output. In this study, a single-stage grid-connected PV
system is designed to enhance power quality. Our approach employs fuzzy
logic in the direct power control (DPC) of a three-phase voltage source
inverter (VSI), enabling seamless integration of the PV connected to the
grid. Additionally, a fuzzy logic-based maximum power point tracking
(MPPT) controller is adopted, which outperforms traditional methods like
incremental conductance (INC) in enhancing solar cell efficiency and
minimizing the response time. Moreover, the inverter's real-time active and
reactive power is directly managed to achieve a unity power factor (UPF).
The system's performance is assessed through MATLAB/Simulink
implementation, showing marked improvement over conventional methods,
particularly in steady-state and varying weather conditions. For solar
irradiances of 500 and 1,000 W/m2
, the results show that the proposed
method reduces the total harmonic distortion (THD) of the injected current
to the grid by approximately 46% and 38% compared to conventional
methods, respectively. Furthermore, we compare the simulation results with
IEEE standards to evaluate the system's grid compatibility.
Enhancing photovoltaic system maximum power point tracking with fuzzy logic-b...IJECEIAES
Photovoltaic systems have emerged as a promising energy resource that
caters to the future needs of society, owing to their renewable, inexhaustible,
and cost-free nature. The power output of these systems relies on solar cell
radiation and temperature. In order to mitigate the dependence on
atmospheric conditions and enhance power tracking, a conventional
approach has been improved by integrating various methods. To optimize
the generation of electricity from solar systems, the maximum power point
tracking (MPPT) technique is employed. To overcome limitations such as
steady-state voltage oscillations and improve transient response, two
traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb
and observe (P&O), have been modified. This research paper aims to
simulate and validate the step size of the proposed modified P&O and FLC
techniques within the MPPT algorithm using MATLAB/Simulink for
efficient power tracking in photovoltaic systems.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
Remote field-programmable gate array laboratory for signal acquisition and de...IJECEIAES
A remote laboratory utilizing field-programmable gate array (FPGA) technologies enhances students’ learning experience anywhere and anytime in embedded system design. Existing remote laboratories prioritize hardware access and visual feedback for observing board behavior after programming, neglecting comprehensive debugging tools to resolve errors that require internal signal acquisition. This paper proposes a novel remote embeddedsystem design approach targeting FPGA technologies that are fully interactive via a web-based platform. Our solution provides FPGA board access and debugging capabilities beyond the visual feedback provided by existing remote laboratories. We implemented a lab module that allows users to seamlessly incorporate into their FPGA design. The module minimizes hardware resource utilization while enabling the acquisition of a large number of data samples from the signal during the experiments by adaptively compressing the signal prior to data transmission. The results demonstrate an average compression ratio of 2.90 across three benchmark signals, indicating efficient signal acquisition and effective debugging and analysis. This method allows users to acquire more data samples than conventional methods. The proposed lab allows students to remotely test and debug their designs, bridging the gap between theory and practice in embedded system design.
Detecting and resolving feature envy through automated machine learning and m...IJECEIAES
Efficiently identifying and resolving code smells enhances software project quality. This paper presents a novel solution, utilizing automated machine learning (AutoML) techniques, to detect code smells and apply move method refactoring. By evaluating code metrics before and after refactoring, we assessed its impact on coupling, complexity, and cohesion. Key contributions of this research include a unique dataset for code smell classification and the development of models using AutoGluon for optimal performance. Furthermore, the study identifies the top 20 influential features in classifying feature envy, a well-known code smell, stemming from excessive reliance on external classes. We also explored how move method refactoring addresses feature envy, revealing reduced coupling and complexity, and improved cohesion, ultimately enhancing code quality. In summary, this research offers an empirical, data-driven approach, integrating AutoML and move method refactoring to optimize software project quality. Insights gained shed light on the benefits of refactoring on code quality and the significance of specific features in detecting feature envy. Future research can expand to explore additional refactoring techniques and a broader range of code metrics, advancing software engineering practices and standards.
Smart monitoring technique for solar cell systems using internet of things ba...IJECEIAES
Rapidly and remotely monitoring and receiving the solar cell systems status parameters, solar irradiance, temperature, and humidity, are critical issues in enhancement their efficiency. Hence, in the present article an improved smart prototype of internet of things (IoT) technique based on embedded system through NodeMCU ESP8266 (ESP-12E) was carried out experimentally. Three different regions at Egypt; Luxor, Cairo, and El-Beheira cities were chosen to study their solar irradiance profile, temperature, and humidity by the proposed IoT system. The monitoring data of solar irradiance, temperature, and humidity were live visualized directly by Ubidots through hypertext transfer protocol (HTTP) protocol. The measured solar power radiation in Luxor, Cairo, and El-Beheira ranged between 216-1000, 245-958, and 187-692 W/m 2 respectively during the solar day. The accuracy and rapidity of obtaining monitoring results using the proposed IoT system made it a strong candidate for application in monitoring solar cell systems. On the other hand, the obtained solar power radiation results of the three considered regions strongly candidate Luxor and Cairo as suitable places to build up a solar cells system station rather than El-Beheira.
An efficient security framework for intrusion detection and prevention in int...IJECEIAES
Over the past few years, the internet of things (IoT) has advanced to connect billions of smart devices to improve quality of life. However, anomalies or malicious intrusions pose several security loopholes, leading to performance degradation and threat to data security in IoT operations. Thereby, IoT security systems must keep an eye on and restrict unwanted events from occurring in the IoT network. Recently, various technical solutions based on machine learning (ML) models have been derived towards identifying and restricting unwanted events in IoT. However, most ML-based approaches are prone to miss-classification due to inappropriate feature selection. Additionally, most ML approaches applied to intrusion detection and prevention consider supervised learning, which requires a large amount of labeled data to be trained. Consequently, such complex datasets are impossible to source in a large network like IoT. To address this problem, this proposed study introduces an efficient learning mechanism to strengthen the IoT security aspects. The proposed algorithm incorporates supervised and unsupervised approaches to improve the learning models for intrusion detection and mitigation. Compared with the related works, the experimental outcome shows that the model performs well in a benchmark dataset. It accomplishes an improved detection accuracy of approximately 99.21%.
Developing a smart system for infant incubators using the internet of things ...IJECEIAES
This research is developing an incubator system that integrates the internet of things and artificial intelligence to improve care for premature babies. The system workflow starts with sensors that collect data from the incubator. Then, the data is sent in real-time to the internet of things (IoT) broker eclipse mosquito using the message queue telemetry transport (MQTT) protocol version 5.0. After that, the data is stored in a database for analysis using the long short-term memory network (LSTM) method and displayed in a web application using an application programming interface (API) service. Furthermore, the experimental results produce as many as 2,880 rows of data stored in the database. The correlation coefficient between the target attribute and other attributes ranges from 0.23 to 0.48. Next, several experiments were conducted to evaluate the model-predicted value on the test data. The best results are obtained using a two-layer LSTM configuration model, each with 60 neurons and a lookback setting 6. This model produces an R 2 value of 0.934, with a root mean square error (RMSE) value of 0.015 and a mean absolute error (MAE) of 0.008. In addition, the R 2 value was also evaluated for each attribute used as input, with a result of values between 0.590 and 0.845.
A review on internet of things-based stingless bee's honey production with im...IJECEIAES
Honey is produced exclusively by honeybees and stingless bees which both are well adapted to tropical and subtropical regions such as Malaysia. Stingless bees are known for producing small amounts of honey and are known for having a unique flavor profile. Problem identified that many stingless bees collapsed due to weather, temperature and environment. It is critical to understand the relationship between the production of stingless bee honey and environmental conditions to improve honey production. Thus, this paper presents a review on stingless bee's honey production and prediction modeling. About 54 previous research has been analyzed and compared in identifying the research gaps. A framework on modeling the prediction of stingless bee honey is derived. The result presents the comparison and analysis on the internet of things (IoT) monitoring systems, honey production estimation, convolution neural networks (CNNs), and automatic identification methods on bee species. It is identified based on image detection method the top best three efficiency presents CNN is at 98.67%, densely connected convolutional networks with YOLO v3 is 97.7%, and DenseNet201 convolutional networks 99.81%. This study is significant to assist the researcher in developing a model for predicting stingless honey produced by bee's output, which is important for a stable economy and food security.
Fuzzy linear programming with the intuitionistic polygonal fuzzy numbersIJECEIAES
In real world applications, data are subject to ambiguity due to several factors; fuzzy sets and fuzzy numbers propose a great tool to model such ambiguity. In case of hesitation, the complement of a membership value in fuzzy numbers can be different from the non-membership value, in which case we can model using intuitionistic fuzzy numbers as they provide flexibility by defining both a membership and a non-membership functions. In this article, we consider the intuitionistic fuzzy linear programming problem with intuitionistic polygonal fuzzy numbers, which is a generalization of the previous polygonal fuzzy numbers found in the literature. We present a modification of the simplex method that can be used to solve any general intuitionistic fuzzy linear programming problem after approximating the problem by an intuitionistic polygonal fuzzy number with n edges. This method is given in a simple tableau formulation, and then applied on numerical examples for clarity.
The performance of artificial intelligence in prostate magnetic resonance im...IJECEIAES
Prostate cancer is the predominant form of cancer observed in men worldwide. The application of magnetic resonance imaging (MRI) as a guidance tool for conducting biopsies has been established as a reliable and well-established approach in the diagnosis of prostate cancer. The diagnostic performance of MRI-guided prostate cancer diagnosis exhibits significant heterogeneity due to the intricate and multi-step nature of the diagnostic pathway. The development of artificial intelligence (AI) models, specifically through the utilization of machine learning techniques such as deep learning, is assuming an increasingly significant role in the field of radiology. In the realm of prostate MRI, a considerable body of literature has been dedicated to the development of various AI algorithms. These algorithms have been specifically designed for tasks such as prostate segmentation, lesion identification, and classification. The overarching objective of these endeavors is to enhance diagnostic performance and foster greater agreement among different observers within MRI scans for the prostate. This review article aims to provide a concise overview of the application of AI in the field of radiology, with a specific focus on its utilization in prostate MRI.
Seizure stage detection of epileptic seizure using convolutional neural networksIJECEIAES
According to the World Health Organization (WHO), seventy million individuals worldwide suffer from epilepsy, a neurological disorder. While electroencephalography (EEG) is crucial for diagnosing epilepsy and monitoring the brain activity of epilepsy patients, it requires a specialist to examine all EEG recordings to find epileptic behavior. This procedure needs an experienced doctor, and a precise epilepsy diagnosis is crucial for appropriate treatment. To identify epileptic seizures, this study employed a convolutional neural network (CNN) based on raw scalp EEG signals to discriminate between preictal, ictal, postictal, and interictal segments. The possibility of these characteristics is explored by examining how well timedomain signals work in the detection of epileptic signals using intracranial Freiburg Hospital (FH), scalp Children's Hospital Boston-Massachusetts Institute of Technology (CHB-MIT) databases, and Temple University Hospital (TUH) EEG. To test the viability of this approach, two types of experiments were carried out. Firstly, binary class classification (preictal, ictal, postictal each versus interictal) and four-class classification (interictal versus preictal versus ictal versus postictal). The average accuracy for stage detection using CHB-MIT database was 84.4%, while the Freiburg database's time-domain signals had an accuracy of 79.7% and the highest accuracy of 94.02% for classification in the TUH EEG database when comparing interictal stage to preictal stage.
Analysis of driving style using self-organizing maps to analyze driver behaviorIJECEIAES
Modern life is strongly associated with the use of cars, but the increase in acceleration speeds and their maneuverability leads to a dangerous driving style for some drivers. In these conditions, the development of a method that allows you to track the behavior of the driver is relevant. The article provides an overview of existing methods and models for assessing the functioning of motor vehicles and driver behavior. Based on this, a combined algorithm for recognizing driving style is proposed. To do this, a set of input data was formed, including 20 descriptive features: About the environment, the driver's behavior and the characteristics of the functioning of the car, collected using OBD II. The generated data set is sent to the Kohonen network, where clustering is performed according to driving style and degree of danger. Getting the driving characteristics into a particular cluster allows you to switch to the private indicators of an individual driver and considering individual driving characteristics. The application of the method allows you to identify potentially dangerous driving styles that can prevent accidents.
Hyperspectral object classification using hybrid spectral-spatial fusion and ...IJECEIAES
Because of its spectral-spatial and temporal resolution of greater areas, hyperspectral imaging (HSI) has found widespread application in the field of object classification. The HSI is typically used to accurately determine an object's physical characteristics as well as to locate related objects with appropriate spectral fingerprints. As a result, the HSI has been extensively applied to object identification in several fields, including surveillance, agricultural monitoring, environmental research, and precision agriculture. However, because of their enormous size, objects require a lot of time to classify; for this reason, both spectral and spatial feature fusion have been completed. The existing classification strategy leads to increased misclassification, and the feature fusion method is unable to preserve semantic object inherent features; This study addresses the research difficulties by introducing a hybrid spectral-spatial fusion (HSSF) technique to minimize feature size while maintaining object intrinsic qualities; Lastly, a soft-margins kernel is proposed for multi-layer deep support vector machine (MLDSVM) to reduce misclassification. The standard Indian pines dataset is used for the experiment, and the outcome demonstrates that the HSSF-MLDSVM model performs substantially better in terms of accuracy and Kappa coefficient.
Fuzzy logic method-based stress detector with blood pressure and body tempera...IJECEIAES
In this study, using the fuzzy logic method, a stress detection tool was created with body temperature and blood pressure parameters as indicators to determine a person's stress level. This tool uses the LM35DZ sensor to detect body temperature, the MPX5100GP sensor to read blood pressure values, and Arduino Uno as a data processor from sensor readings which are then calculated using the fuzzy logic method as a stress level decisionmaker. The resulting output measures blood pressure, body temperature, and the stress level experienced by a person, which will be displayed on the liquid crystal display. Based on the results of testing the body temperature parameter, the highest error generated was 1.17%, and for the blood pressure parameter, the highest error was 2.5% for systole and 0.93% for diastole. Furthermore, testing the stress level displayed on the tool is compared to the depression, anxiety, and stress scales 42 (DASS 42), a psychological stress measuring instrument. From the results of testing the tool with the questionnaire, the average conformity level is 74%.
Democratizing Fuzzing at Scale by Abhishek Aryaabh.arya
Presented at NUS: Fuzzing and Software Security Summer School 2024
This keynote talks about the democratization of fuzzing at scale, highlighting the collaboration between open source communities, academia, and industry to advance the field of fuzzing. It delves into the history of fuzzing, the development of scalable fuzzing platforms, and the empowerment of community-driven research. The talk will further discuss recent advancements leveraging AI/ML and offer insights into the future evolution of the fuzzing landscape.
Student information management system project report ii.pdfKamal Acharya
Our project explains about the student management. This project mainly explains the various actions related to student details. This project shows some ease in adding, editing and deleting the student details. It also provides a less time consuming process for viewing, adding, editing and deleting the marks of the students.
Explore the innovative world of trenchless pipe repair with our comprehensive guide, "The Benefits and Techniques of Trenchless Pipe Repair." This document delves into the modern methods of repairing underground pipes without the need for extensive excavation, highlighting the numerous advantages and the latest techniques used in the industry.
Learn about the cost savings, reduced environmental impact, and minimal disruption associated with trenchless technology. Discover detailed explanations of popular techniques such as pipe bursting, cured-in-place pipe (CIPP) lining, and directional drilling. Understand how these methods can be applied to various types of infrastructure, from residential plumbing to large-scale municipal systems.
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Privacy-aware secured discrete framework in wireless sensor network
1. International Journal of Electrical and Computer Engineering (IJECE)
Vol. 14, No. 1, February 2024, pp. 75~85
ISSN: 2088-8708, DOI: 10.11591/ijece.v14i1.pp75-85 75
Journal homepage: http://ijece.iaescore.com
Privacy-aware secured discrete framework in wireless sensor
network
Nandini Sonnappa, Kempanna Muniyegowda
Department of Computer Science and Engineering, Bangalore Institute of Technology, Bangalore, India
Article Info ABSTRACT
Article history:
Received Jun 8, 2023
Revised Jul 12, 2023
Accepted Jul 17, 2023
Rapid expansion of wireless sensor network-internet of things (WSN-IoT) in
terms of application and technologies has led to wide research considering
efficiency and security aspects. Considering the efficiency approach such as
data aggregation along with consensus mechanism has been one of the
efficient and secure approaches, however, privacy has been one of major
concern and it remains an open issue due to low classification and high
misclassification rate. This research work presents the privacy and reliable
aware discrete (PRD-aggregation) framework to protect and secure the
privacy of the node. It works by initializing the particular variable for each
node and defining the threshold; further nodes update their state through the
functions, and later consensus is developed among the sensor nodes, which
further updates. The novelty of PRD is discretized transmission for
efficiency and security. PRD-aggregation offers reliability through efficient
termination criteria and avoidance of transmission failure. PRD-aggregation
framework is evaluated considering the number of deceptive nodes for
securing the node in the network. Furthermore, comparative analysis proves
the marginal improvisation in terms of discussed parameter against the
existing protocol.
Keywords:
Aggregation
Internet of things
Nodes
Security
Wireless sensor network
This is an open access article under the CC BY-SA license.
Corresponding Author:
Nandini Sonnappa
Department of Computer Science and Engineering, Bangalore Institute of Technology
Bangalore, India
Email: nandinis@sjcit.ac.in
1. INTRODUCTION
Presently, wireless sensory networks (WSN) are utilized at the forefront of communication systems
that include environmental monitoring, smart home automation, and industries. This technology has a widely
increasing potential concerning applications of real-time due to its small size, inexpensive and easy
deployment [1], [2]. The design of WSNs is dependent on various situations for their application. In
applications of the industry as well as automation of the home, in which there is no constraint of energy,
delivery packets are the most essential for designing a network. However, in an unsafe environment in which
there is a battery that is not replaced or recharged which includes mining, which increased the lifetime of the
network, is the main factor in designing the network. Although, the deployed area size has an important role
in the design of the WSN. Considering smaller areas, the transmission of the packets is done directly from the
sensory nodes to the base station or sinks nodes, whereas, in large areas, the transmission of packets happens
via various intermediate nodes to sink nodes [3].
Additionally, the system that is enabled using internet of things (IoT) has an ability for
interconnection of various ‘things’ for effective communication as well as sharing of data for one network,
there is a wide number of advantages that have attracted various technologists [4], [5]. In the short term, IoT
2. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 14, No. 1, February 2024: 75-85
76
systems are an important part of various sectors that include healthcare, manufacturing, logistics as well as
transportation, which enable crucial infrastructure of the IoT [6]. The majority of the intelligent control nodes
are linked to the internet in the IoT technology, such nodes are transmitters or sensors that can retrieve data
from the other systems and process it without any intervention. Numerous IoT applications are adopted to
improve system efficiency and quality in industrial management, transport, and medical; because of the
increasing prevalence of the IoT [1]–[3]. IoT technology focuses on multiple activities to achieve the
objectives generated through smart services. Figure 1 shows the WSN and IoT integration working.
Intelligent devices can interact with the real world through intelligent operations so that consumers may get
the proper service whenever and wherever they need it.
Figure 1. WSN and IoT integration working
Figure 1 shows the integrated architecture of WSN-IoT; it comprises several modules. WSN is
where several sensor networks are connected for efficient transmission through the gateway. The other two
blocks are smart objects through which data are communicated to humans. Considering the increased
complexity in architecture, several uses of heterogeneous devices and threats towards privacy are difficult to
be identified, access, and mitigated. However, the large-scale increased complexity of IoT systems introduces
a deluge of data. Confidential and sensitive data have been constantly shared among the networks, and
privacy, as well as security, are huge concerns that are prevailing in the IoT's crucial infrastructure [7]. Any
of the attacks on cyber systems that are vulnerable could compromise the integrity and privacy of huge
amounts of data that is sensitive.
The frequency and types of attacks have increased because of substantial technological
advancements. Attackers frequently take advantage of the variability in the IoT to create trust challenges and
modify behavior to mislead users about the dependability of the sensors and the services offered through
them. Moreover, the variety and complexity of IoT systems as well as resource limitations have produced
enormous issues in terms of reliability, confidentiality, and transparency, all of which are crucial for the
successful deployment of IoT [5]. As a result, the trust evaluation system is used to isolate unreliable objects
and identify dishonest behavior. When taking any action, it also overcomes the possibility of ambiguity and
minimizes the risks. This can enable IoT infrastructure operation in a controllable environment and prevent
unpredictable events and service failures [4]–[6]. Without a reliable security mechanism that prevents the
creation of harmful models or at least lessens their influence, IoT systems are unlikely to be widely adopted
[6], [7]. As a result, IoT security uses systems for authentication and encryption. Strong authentication and
encryption technologies help to address several IoT security concerns. The techniques for secure message
transmission between nodes, such as authentication and encryption, serve as the first line of protection
against outside threats [8], [9]. These defenses can stop and identify external attacks, but they are unable to
deal with insider threats and hostile network nodes. In practice, internal attackers can circumvent these
defenses by gaining access to the common key and initiating several attacks against the IoT network.
Because of this reason, it is essential to ensure trust to counter internal attacks in the IoT environment.
Approaches towards the preservation of privacy have gathered attention over the years due to progress
towards information technology that has threatened individual privacy. Although, considering the rise
3. Int J Elec & Comp Eng ISSN: 2088-8708
Privacy-aware secured discrete framework in wireless sensor network (Nandini Sonnappa)
77
towards the adoption of edge computing as well as fog paradigms for IoT crucial information has led to
decreased latency, awareness of location, communication, and data sharing in real-time, and quality of
service (QoS) [10], [11]. The devices used for edge computing in IoT crucial information are prone to attacks
of privacy [12]. Considering this approach, many techniques for the preservation of privacy that include
traditional as well as modern deep learning algorithms are proposed [13]. The existing deep learning
methodologies that are implemented based on fog/edge computing for crucial information solutions need
expensive computation.
There are various kinds of attacks on IoT crucial information that include attacks for denial of
service, Sybil attacks [8], [9]. Access level-based cyber-attacks for IoT crucial networks are classified as
passive and active attacks [10]. Active attacks, which are also termed attacks that are security oriented,
derange the communication of the network by avoiding the available security protection. On the contrary,
passive attacks are termed as attacks that are privacy-oriented such as networks eavesdropping without any
disturbance for gaining illicit access to confidential sensitive information. The widely growing IoT crucial
information is now prone to various attacks by hackers as well as organized crime syndicates. The growth in
the count of threats towards privacy that are targeted towards IoT crucial information results in motivation
for the development of various solutions. Although, most of the security approaches that are proposed have
the absence of applicability, which may be the result of the complexity of computation, expense, and other
factors that are related. Motivated by the above issues, the contribution of the research is given as follows:
i) this research takes privacy, security, and reliability into account for aggregation in WSN based IoT
environment and develops a privacy and reliable aware discrete (PRD)-aggregation framework; ii) PRD-
aggregation framework is an integrated framework that utilizes the designed constraint, discrete, time, and
event for preserving the nodes' privacy; furthermore, discrete based mechanism utilizes the threshold setting
for nodes for detection at the packet level and node level; and iii) PRD-aggregation is evaluated by inducing
the deceptive nodes in the network for detection of dishonest nodes for classification and misclassification of
nodes identification.
This research is organized as follows: The first section starts with a background of IoT, sensor
nodes, and issues of security and privacy of the nodes and the section concludes with research motivation and
contribution. The second section presents the existing approach along with its shortcoming. The third section
presents the mathematical modeling of the PR-aggregation model and the fourth section presents the
performance evaluation.
2. RELATED WORK
The confidentiality issue of malicious node identification is solved in WSN, in [14] the algorithm is
improvised for the neighbor weight trust detection (NWTD) mechanism. This algorithm in parallel updates
the trust value to ensure the trust degree for the nodes and fix a minimum peak value in an acceptable range.
However, this is capable of ensuring the segmentation of malicious nodes, the main aim of this approach the
malicious node detection in WSN’s states that in [15] a trusted method is developed based on Dempster-
Shafer (D-S) evidence theory is developed by incorporating the indirect and direct trust of third–party nodes
to assess the strength of the network. The validation of the data packet, in [16] and [17] based on evaluation
have developed a trust model that is focused on the computation of trust degree to handle either direct or
indirect levels of trust while taking into account the internal attacks that wireless sensor networks are
susceptible. This method minimizes the amount of energy used by the network and generates the trusted
benchmark to simplify decision-making, which is easier by frequently updating the degree of trust. To assure
network security and dependability, it may further identify between malicious nodes and aging nodes. To
reduce the uncertainty of the decisions made by the conventional trust approach, it analyses the signal
success rate, node latency, accuracy, and fairness as trust metrics. A multi-attribute trust model was
developed in [18] employing fuzzy processing to compute the overall trust value of each node; this
demonstrated that the conclusion is accurate. A novel trust management system founded on the D-S evidence
theory is discussed herein [19].
The D-S theory was used to analyze the spatiotemporal correlation of data collected by nearby
sensor nodes to develop the trust model. Consequently, an evaluation is made to determine which nodes are
malicious. In [20], the challenges are addressed by considering the single detection function and failure of the
malicious node detection mechanism by introducing a novel malicious node detection model to counter the
vicious libel behavior of high-reputation nodes within current WSNs. This model illustrated the Beta
Distribution reputation distribution and the implicit reliability of third-party nodes. This guarantees the
precise detection of malicious nodes; it additionally incorporates the trust values, which correspond to
different attack types. In [20], a methodology of truth discovery for preserving privacy is proposed, although,
the client overhead is high. In [21], a two-layer methodology is proposed for fulfilling the requirement of
protecting the privacy of the user. In [22], a novel lightweight framework of truth discovery for preserving
4. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 14, No. 1, February 2024: 75-85
78
privacy is proposed that is used for the implementation of two cloud platforms that are non-colluding as well
as adopting a homomorphic cryptosystem. In [23], a novel data poisoning disguise attack (DDPA) is
proposed against private systems of crowd sensing that are empowered with the methodology of truth
discovery. A stealth strategy is proposed that is, the malicious characteristics are disguised for avoiding the
detection of methods for truth discovery. Along with this strategy of stealth, the limitation of maximizing the
effectiveness of the attack is naturally avoided using optimization problems at the bi-level via structuring that
is resolved by an alternate optimization algorithm. In [24], a novel semantic awareness for the preservation of
privacy for the trajectory of online location sharing method called Semantic-awareness information-
theoretical privacy (SEITP), for the protection of privacy of data as well as semantic during semantic
awareness of data is utilized can be preserved completely [25].
3. PROPOSED METHOD
The data that has been gathered from IoT devices must be required for analysis as well as utilization.
However, the gathered data could also have information that is sensitive and personal to the user, this hinders
the privacy protection of the users. The unwillingness of the users to contribute their information affects the
usability of the data. Privacy and reliability while aggregation has been one of the wide research using the
consensus-based approach where nodes are required to exchange and disclose their state information to its
adjacent node. However, this directly involves the privacy and reliability of nodes. This research work aims
to develop a PRD-aggregation mechanism to achieve the trade-off among privacy and aims to guarantee
convergence. Moreover, secure data aggregation has been carried out in previous research work; this work
utilizes a secured and efficient mechanism and further provides privacy and reliability for the user. Figure 2
presents the proposed PRD model that comprises various modules. At first, the system model is designed
based on the connected graph; further total number of variables is selected along with the selection of
adjacent nodes. Furthermore, considering the variable, nodes state is updated and constraints are checked and
verified.
Figure 2. Proposed PR-model
3.1. System modeling and problem definition
This section provides the mathematical foundation for modeling among the sensor nodes in the
WSN, Let’s consider any particular network Q(Q ≥ 2) that communicates with adjacent nodes; also,
communication is established through the designed directed graph. In a designed graph, Jg = (Y, H), where
Y = [y1, y2, y3, … . . yq] and q is the particular node set with G as the edges. Furthermore, we consider
particular time step m ∈ C ≥ 0 with each node maintaining its particular state. Directed edge between ym and
yl is denoted through (1).
𝑜𝑙𝑚 ≜ (𝑦𝑙𝑦𝑚) ∈ 𝐻 (1)
The equation (1) validates that the sensor node 𝑦𝑚 can receive information fromyl; also, it is assumed that
graph designs are connected such that there exists a direct path between the two distinctive nodes. Moreover,
the sensor node set which can directly transmit to the node is known as an inner adjacent set of 𝑦𝑚 and this
can be represented as Q′m = [yl ∈ Y| (yl, ym) ∈ H]; also, sensor nodes that can receive direct information
from node 𝑦𝑚 is known as an outer adjacent set and denoted as Q′′m. Furthermore, the behavior of sensor
nodes in the network is discussed. Consider the particular strong connected graph as designed earlier, every
5. Int J Elec & Comp Eng ISSN: 2088-8708
Privacy-aware secured discrete framework in wireless sensor network (Nandini Sonnappa)
79
node has a certain stage denoted as bl[0], thus nodes are required to compute the (2) that satisfies the
verifiable and reliable criteria.
𝐵′
= 𝑞(∑
𝑞
𝑜−1 𝑏𝑜[𝑜])−1
(2)
The main aim of this research work is to design a particular strategy for a verifiable and reliable strategy for
nodes yk ∈ Ys/Yf while communicating with the nodes. Moreover, the problem is designed to compute the B′
as in (1). Moreover, communication takes only among the nodes, which are adjacent to the designed graph,
and represents topology. A particular node in set 𝑌 could be deceptive and tries to enter the network and
violate privacy by trying to violate confidentiality, which means it tries to identify the particular stateb[0].
Hence, Privacy can be defined as the node's and network's capability to hide the information, thus proposed
model tends to preserve privacy by hiding their confidentiality.
3.2. Discretizing and consensus
Considering the characteristics of data sensing in the WSN-based IoT model, the proposed model is
designed such that given time step m ∈ B≥0, every node holds the characteristics bm
v [n], cm
v [n], cm
v [n]. In here
tv
is considered as yet another variable designed for output. Furthermore, it is assumed that each sensor node
is aware of its other adjacent nodes and directly communicates with them; each node gets assigned with a
particular order to each of the outgoing edges 𝑝𝑜𝑚
. Here 𝑦𝑛 ∈ 𝑄𝑚
′
, specifically to the link (yo, ym) for node
𝑆𝑛𝑚
depicted by 𝑆𝑜𝑚
(where {𝑆𝑜𝑚
|𝑦𝑜 ∈ 𝑄𝑚
′
} = {0,1, …. . , 𝐺𝑚
′
− 1}). The proposed model develops the
consensus model to process and transmit the information for efficient communication and obtains 𝑡𝑣
which is
equivalent to the absolute average of the initial states of the node after a certain number of steps. Moreover, it
is assumed that every sensor node in the network holds initial states bm[0] ∈ C ; furthermore, at every time
step 𝑦𝑚 ∈ 𝑌 retains the parameters 𝑏𝑚[𝑛] ∈ 𝐶and 𝑐𝑚[𝑛] ∈ 𝐶 and state variables 𝑏𝑚
𝑣 [𝑛] ∈ 𝐶 and 𝑐𝑚
𝑣 [𝑛] ∈ 𝐶
and 𝑡𝑛
𝑣[𝑛] = 𝑏𝑚
𝑣 [𝑛]/𝑐𝑚
𝑣 [𝑛].
𝑏𝑚[𝑛 + 1] = 𝑏𝑚[𝑛] + ∑𝑦𝑙∈𝑄𝑚
′′ 1𝑚𝑙[𝑛]𝑏𝑙[𝑚] (3)
𝑐𝑚[𝑛 + 1] = 𝑐𝑚[𝑛] + ∑𝑦𝑙∈𝑄𝑚
′′ 1𝑚𝑙[𝑛]𝑐𝑙[𝑛] (4)
In (3) and (4), here 1𝑚𝑙[𝑛] is zero in case of no communication at the node 𝑦𝑚 from the neighbor 𝑦𝑙 at
iteration 𝑚, the following cases are encountered. The proposed model develops the consensus model to
process and transmit the information for efficient communication and obtains 𝑡𝑣
which is equivalent to the
absolute average of the initial states of the node after a certain number of steps. It then transmits 𝑏𝑚
𝑣 [𝑛 + 1],
𝑐𝑚[𝑛 + 1], to an adjacent 𝑦𝑛 ∈ 𝑄𝑚
′
and set the value bm[n + 1] = 0 and 𝑐𝑏[𝑛 + 1] = 0. Two cases are
mentioned here.
− First case: 𝑐𝑚[𝑛 + 1] > 𝑐𝑚
𝑣 [𝑛],
− Second case: 𝑐𝑚[𝑛 + 1] > 𝑐𝑚
𝑣 [𝑛] and 𝑏𝑚[𝑛 + 1] ≥ 𝑏𝑚
𝑣 [𝑛] is satisfied, the node 𝑥𝑏 updates the state
variables as (5),
𝑐𝑚
𝑣 [𝑛 + 1] = 𝑐𝑚[𝑛 + 1], 𝑏𝑚
𝑣 [𝑛 + 1] = 𝑏𝑚[𝑛 + 1], 𝑡𝑚
𝑣 [𝑛 + 1] = 𝑏𝑚
𝑣 [𝑛 + 1](𝑐𝑚[𝑛 + 1])−1
(5)
3.3. Designing constraints for privacy, reliability, and verifiability
In this section, we develop a constraint, which aims to preserve the node's information, and any
malicious nodes, which aim to obtain information, get removed from the network. Moreover, the main
intention of the defined algorithm is to compute the B′. The proposed model follows the event-based
approach for security modeling i.e., whenever there is a violation, the event gets triggered. The existing
privacy preservation approach utilizes the initial states of the node as b′′′[0] = bm[0] + xm. However, due to
the imitation of preservation of privacy, the proposed model introduces the negative variable 𝑥𝑚 such that it
guarantees the computation of the consensus approach in a certain number of steps. Furthermore, each sensor
node holds its privacy value parameter 𝑥𝑚[𝑛], steps 𝑂𝑚, counter variable, and transmission counter variable
𝑓
𝑚. The absolute value of the initial value and the number of added variables 𝑂𝑚 is required to be larger than
the adjacent node 𝑦𝑚. Considering initialization, every node 𝑦𝑚 selects the steps and variable parameter to
satisfy the given below condition:
Condition 1: Adding steps 𝑂𝑚 in the variable of each node 𝑦𝑚 required to be larger than or equal to 𝑦𝑚’s
degree such that the adjacent node receives at least one piece of information.
𝑂𝑚 ≥ 𝐺𝑚
′
(6)
6. ISSN: 2088-8708
Int J Elec & Comp Eng, Vol. 14, No. 1, February 2024: 75-85
80
Condition 2: Moreover, the accumulated variable is infused in computation through the node 𝑦𝑚 such that the
node state can be computed without any error.
𝑥𝑚 = − ∑𝑂𝑚
𝑜𝑚
𝑥𝑚[𝑜𝑚] (7)
Constraint 3: Variable 𝑥𝑚[𝑜𝑚] is induced to the network by each node based on the event, which needs to be
non-negative.
𝑥𝑚[𝑜𝑚] ≥ 0, 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑜𝑚𝜖[0, 𝑂𝑚] (8)
Constraint 4: Node 𝑥𝑚 stops inducing variables such that states can be calculated as (9):
𝑥𝑚[𝑜𝑚] = 0, 𝑓𝑜𝑟 𝑎𝑙𝑙 𝑜𝑚 ∉ [0, 𝑂𝑚] (9)
The above constraints indicate that the initial variable is induced in the network hence it is negative and
satisfies 𝑢𝑗 ≥ 𝐺𝑚
′′
. Furthermore, while data transmission constraint 1 and constraint 2 hold for each node after
certain steps, and in case of violation it will fail to compute the average consensus. The proposed algorithm
has a value transfer process in which each node has a connected digraph 𝐻𝑑 = (𝑋, 𝑌), which performs
executions according to a set of the event-triggered conditions. Each node here 𝑥𝑏 ∈ 𝑋𝑂 to ensure privacy in
these steps.
− A counter 𝑜𝑚 is set to zero and sets the total number of offset-added steps 𝑂𝑚 such as 𝑂𝑚 ≥ 𝐽𝑚
′
and the
set of (𝑂𝑚 + 1) with a positive offset 𝑥𝑚[𝑜𝑚] > 0, where 𝑜𝑚 ∈ {0,1,2 … . , 𝑂𝑚}. The initial negative offset
value 𝑥𝑚 injects the initial state value 𝑏𝑙[0] to 𝑥𝑚 = − ∑𝑂𝑚
𝑜𝑚=0 𝑦𝑚[𝑜𝑚].
− To select the 𝑦𝑜 ∈ 𝑄𝑚
′
in the order 𝑆𝑜𝑚 to transmit 𝑐𝑘[0] and 𝑏′′′
[0] = 𝑏𝑚[0] + 𝑥𝑚 + 𝑥𝑚[0] to the out-
neighbor. Then it sets the value to 𝑐′′′𝑚[0] = 0, 𝑐𝑚[0] = 0, and 𝑜𝑚 = 𝑜𝑚 + 1.
− The algorithm is executed, at each step 𝑛, node 𝑦𝑚 to receive a set of variables 𝑏′′′𝑙[𝑛] and 𝑐𝑙[𝑛] for each-
in neighbor 𝑦𝑙 ∈ 𝑄𝑚
′′′
. The node 𝑦𝑚 updates the variables with 𝑏′′′𝑚[𝑛] to check if the events-triggered
condition holds. If true then 𝑥𝑚[𝑜𝑚] to 𝑥𝑚[𝑛 + 1] and enhances the offset counter 𝑜𝑚 by one. It then sets
the variables 𝑏𝑚
𝑣 [𝑛 + 1] and 𝑐𝑚
𝑣 [𝑛 + 1] irrespective of 𝑏𝑚
𝑣 [𝑛 + 1] and 𝑐𝑚
𝑣 [Ƥ + 1]. Then it transmits to an
out-neighbor 𝑏′′′𝑚[𝑛 + 1] and 𝑐𝑚[𝑛 + 1] to an out-neighbor in pre-trained order. Here 𝑦𝑚 holds the
𝑏𝑚[𝑛 + 1] and 𝑐𝑚[𝑛 + 1]., No message is received from any of–its neighbors, and with no transmission,
the mass variable retains the same.
3.4. PRD-aggregation algorithm
This research work aims to develop a PRD-aggregation mechanism to achieve the trade-off among
privacy and aims to guarantee convergence. Moreover, secure data aggregation has been carried out in
previous research work. This work utilizes a secured and efficient mechanism and further provides privacy
and reliability for the user. Input is taken as the connected graph 𝐽𝑔 = (𝑌, 𝐻) with 𝑞 = |𝐻| edges along with
the initial state of 𝐵𝑙 [0] ∈ 𝐶
Step 1: Assigning a particular order 𝑅𝑜𝑙
in a given set {0,1, … 𝐺𝑚
′′ } for each adjacent node 𝑦𝑜 ∈ 𝑄𝑚
′′
Step 2: Setting up the counter 𝑓
𝑚 = 0 along with index (priority based) ℎ𝑚 to 𝑓
𝑚
Step 3: Setting up the counter 𝑜𝑚 = 0, selects 𝑂𝑚 ∈ 𝐶 > 0 where 𝑂𝑚 ≥ 𝐺𝑚
′′
Step 4: Setting up 𝐵𝑚
′
= 𝐵𝑚[0] + 𝑥𝑚, 𝐶𝑚[0] = 1, 𝐶𝑚
𝑣 [0] = 1 & 𝐶𝑚
𝑣 [0] = 𝐵𝑚
′
[0]
Step 5: Choosing adjacent node 𝑦𝑜 ∈ 𝑄𝑚
′′
such that 𝑅𝑜𝑚 = ℎ𝑚 and transmit 𝐶𝑚[0] and 𝐶𝑚
′
+ 𝑥𝑚[0] to a
particular adjacent node. Furthermore, setting 𝐵𝑚
′ [0] = 0, 𝐶𝑚
′ [0] = 0, 𝑛𝑚 = 𝑛𝑚 + 1
Step 6: Setting 𝑓
𝑚 = 𝑓
𝑚 + 1 and ℎ𝑚 = 𝑓
𝑚 𝑚𝑜𝑑 𝑂𝑚
′′
Step 7: Considering the iteration of 𝑛 = 0,1,2 … . 𝑒𝑣𝑒𝑟𝑦 node ym carries out the following operation.
Step 8: If it receives Bl
′[N],Cl[N] from an adjacent node ym ∈ Qm
′′′
and updation is carried out with (1) and
(2).
Step 9: If (1) and (2) hold then transmit the information about nodes for preserving privacy.
Step 10: Output as tm
v
[n] for each node 𝑦𝑚 ∈ 𝑌.
In the above algorithm, the first 𝑜𝑚 to zero and select the total number of variables adding with 𝑂𝑚
steps such that 𝑂𝑚 ≥ 𝐺𝑚
′′
and with (𝑂𝑚 + 1) positive variable 𝑥𝑚[𝑜𝑚] > 0. Furthermore, considering 𝑦𝑜 ∈
𝑄𝑚
′
following order 𝑆𝑜𝑚 and transmit 𝐵𝑚
′
[0] and 𝐵𝑚
′
[0]. Furthermore, while executing the algorithm, at every
step 𝑚, node 𝑦𝑚 receive a set of requests for packet transmission from each adjacent node, conditions are
checked for verification, and if holds then the data packets are transmitted and the node remains else nodes
are discarded out of the network.
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4. PERFORMANCE EVALUATION
While performing the aggregation it is very important, that reliable and truthful data be collected.
PRD-aggregation aims to assure the privacy of sensor nodes as well the reliability of the data. Moreover,
PRD-aggregation is evaluated considering the dishonest sensor nodes. It is evaluated on the system
configuration that includes 2 TB of the hard disk loaded with 16 GB of random-access memory (RAM) along
with 2 GB NVidia Cuda-enabled graphics. The proposed model here works on evaluating an incorrect
identification of the node that results in unevenness in the network by accommodating various parameters
like identification of the correct node, identification of the wrong node, and computing the throughput for 30,
40, and 50 nodes. Additionally, a comparative analysis is done between the proposed model with the existing
model to ensure the model's security and efficiency and conclude that our proposed system performs better
than the existing system.
4.1. Energy utilization
Figure 3 shows the utilization of energy over the deceptive nodes, the graph is plotted for energy
utilization by the deceptive nodes for 30, 40, and 50 nodes. For 30 nodes there is a steep increase in the after
4.3 value, whereas for 40 nodes there is a steep rise after 4.5 value. For 50 nodes, there exists a steep rise
after 4.9 value. An overall comparison is shown below for 30 40 and 50 nodes.
Figure 3. Energy utilization of deceptive nodes
4.2. Correct identification
Identification of node and packet marks the evaluation and performance of the PRD-Aggregation
model. This section evaluates the security framework based on packet level and node level. The correct nodes
are identified wherein a comparison is made between the existing system and the proposed system by
evaluating the correct identification of nodes with 30, 40, and 50 nodes.
4.3. Packet level
In this section, the packets are identified wherein a comparison is made between the existing system
and the proposed system by evaluating the comparison with 30, 40, and 50 nodes. Figure 4 shows the
comparison of the stated above; in the context of 30, 40, and 50 compromised nodes, the existing system
detects 70, 76, and 77 sensor nodes respectively. In the context of 30, 40, and 50 compromised nodes, the
proposed model identifies 89, 97, and 96 nodes respectively.
4.4. Node level
In this section, the correct nodes are identified wherein a comparison is made between the existing
system and the proposed system by evaluating the correct identification of nodes with 30, 40, and 50 nodes.
Figure 5 shows the comparison of the stated above; in the context of 30, 40, and 50 compromised nodes, the
existing system detects 41.75 and 66 sensor nodes respectively. In the context of 30, 40, and 50 compromised
nodes, the proposed model identifies 97.99 and 97 nodes respectively.
4.5. Wrong node identification
Figure 6 depicts the wrong identification of nodes for 30, 40, and 50 sensor nodes. In 30 nodes
context, the existing model identifies 34 wrong nodes whereas the proposed model wrongly identifies
4 nodes. In 40 nodes, the existing model wrongly identifies 36 nodes whereas the proposed model wrongly
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identifies 2 nodes. In 50 nodes context, the existing model wrongly identifies 35 wrong nodes whereas the
proposed model wrongly identifies 4 nodes.
Figure 4. Packet level classification Figure 5. Correct node identification
Figure 6. Wrong node identification
4.6. Throughput
Throughput is defined as the amount of work done in a specific amount of time; it displays the
models' efficiency. This section evaluates the throughput parameter at the packet level and node level.
Throughput_packet_level is identified wherein a comparison is made between the existing system and the
proposed system.
4.7. Packet level
In this section, the throughput_packet_level is identified wherein a comparison is made between the
existing system and the proposed system by evaluating the comparison with 30, 40, and 50 nodes. Figure 7
shows the comparison of the stated above; in the context of 30 compromised nodes, the existing system
detects 0.266 packet_level and the proposed model identifies 0.3382 packet_level. Consequently, in the
context of 40 sensor nodes, the existing system identifies 0.2128 packet_level whereas the proposed model
identifies 0.2716 packet_level. For 50 sensor nodes, the existing system identifies 0.1155 packet_level
whereas the proposed model identifies 0.144 packet_level.
4.8. Node level
Figure 8 shows the throughput comparison for 30, 40, and 50 sensor nodes. In the case of 30
compromised nodes, the throughput of the existing model is 0.123. For the proposed model, it is 1.09933. In
the case of 40 compromised nodes, the throughput of the existing model is 0.3 and for the proposed model, it
is 0.891. In the case of 50 compromised nodes, the throughput of the existing model is 0.33 and for the
proposed model, it is 0.693.
4.9. Comparative analysis
PRD-aggregation framework is evaluated in the previous section and analyzed in this section.
Comparative analysis is carried out by analyzing the performance enhancement over the low-energy adaptive
clustering hierarchy (LEACH) protocol. Several parameters are mentioned for the comparative analysis.
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83
Figure 7. Throughput packet_level comparison Figure 8. Throughput comparison
4.10. Improvisation over correctly classified nodes
This section displays the comparative analysis and shows the percentage improvisation for the
proposed model from the existing model. Table 1 shows the deceptive nodes improvisation table. The
improvisation is carried out on correct node identification for 30 nodes is 8,159%. The improvisation for 50
nodes the improvisation is 2.758% for 50 nodes the improvisation is 3,803%.
4.11. Improvisation over wrong classified nodes
Table 2 shows the wrong node identification. For wrong node identification, the improvisation for
30 nodes is 1.25%. The improvisation for 40 nodes is 1.05263%. The improvisation for 50 nodes is 15.89%.
Above mentioned table shows the improvisation.
Table 1. Deceptive nodes improvisation table
Deceptive nodes improvisation table
Deceptive nodes Improvisation
30 8.159
40 2.758
50 15.78
Table 2. Shows the wrong node identification
Wrong node identification
Wrong node identification Improvisation
30 1.25%
40 1.05263%
50 15.8%
4.12. Throughput improvisation
For throughput_packet_level, the improvisation for 30 nodes is 2.38%, and for 40 nodes, the
improvisation is 2.427%. For 50 nodes, it is 2.196%. For throughput at the node level. Table 3 shows the
throughput performance. The improvisation for 30 nodes is 15.95%, for 40 nodes, the improvisation is
9.924%, and for 50 nodes, it is 7.096%.
Table 3. Throughput performance
Deceptive nodes Packet level (improvisation in percentage) Node level (Improvisation in percentage)
30 2.38 15.95
40 2.42 9.92
50 2.19 7.096
5. CONCLUSION
Privacy has been one of the major concerns in data transmission, and aggregation due to the
adoption of a consensus-based mechanism for efficient operation; this research work develops a novel
mechanism PRD-aggregation mechanism for ensuring the sensor nodes' privacy to enhance the
confidentiality. The PRD-aggregation novelty lies in the optimization of the consensus approach through the
proposed algorithm. PRD-aggregation framework is evaluated at node and packet level for security
considering 30, 40, and 50 deceptive nodes. Moreover, the evaluation shows the significant improvisation
over the existing leach protocol with classification, misclassification, and throughput. In terms of throughput,
the PRD-aggregation framework achieves improvisation of 2-2.5 at the packet level whereas near or more
than 10% at the node level. The future scope of research lies in the adoption of data integrity technologies
such as blockchain due to the rise of deep learning-based attack models.
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ACKNOWLEDGMENT
I would like to express our sincere gratitude to all those who have supported and contributed to this
research project. Primarily, I extend our heartfelt thanks to our guide for his unwavering guidance, invaluable
insights, and encouragement throughout the research process. No funding is raised for this research.
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BIOGRAPHIES OF AUTHORS
Nandini Sonnappa received the B.Eng. degree in information science and
engineering from Visvesvaraya Technological University, Belagaum, and Karnataka state in
2008 and the M.Tech. Degree in computer science and engineering from Visvesvaraya
Technological University, Belagaum, Karnataka state in 2011 and pursuing Ph.D. in
Visvesvaraya Technological University, Belagaum, and Karnataka. Currently, she is an
Assistant Professor at the Department of Information Science and Engineering, S J C Institute
of Technology, Visveswaraya technological University. Her research interests include data
communication, data structures and applications, cryptography and network security, cyber
security, cloud computing, and IoT. She can be contacted at email: nandinis@sjcit.ac.in.
Kempanna Muniyegowda completed Ph.D. in Karpagam University in the year
2016 in the field of network security recognized as research guide under VTU University NA
students are awarded Ph.D. and Three number of students are pursuing Ph.D. under my
guidance. Major areas of research interest are network security and web security. Published 09
number of papers in recognized journals/conferences. His research interests include data
communication, cryptography and network security, cyber security, cloud computing, and IoT.
lifetime Member in International Association of Engineers (IAENG), Member Number:
269338. He can be contacted at email: kempsindia@gmail.com and kempannam@bit-
bangalore.edu.in.