This document provides an overview of a seminar presentation on fog computing given by Mahantesh Hiremath at Jain College of Engineering. The presentation covered introductions to fog computing and existing cloud systems, advantages of a proposed fog computing system including low latency and location awareness, security issues in cloud systems that fog computing aims to address through techniques like user behavior profiling and decoy systems, examples of fog computing applications in connected vehicles and smart grids, privacy issues in smart grids, and conclusions on how fog computing provides unprecedented security in cloud systems and social networks.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network .This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider.
For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
CONCLUSION
This proposal of monitoring data access patterns by profiling user behavior to determine if and when a malicious insider illegitimately accesses someone’s documents in a Cloud service. Decoy documents stored in the Cloud alongside the user’s real data also serve as sensors to detect illegitimate access. Once unauthorized data access or exposure is suspected, and later verified, with challenge questions for instance, this inundate the malicious insider with bogus information in order to dilute the user’s real data. Such preventive attacks that rely on disinformation technology could provide unprecedented levels of security in the Cloud and in social networks.
Fog computing is defined as a decentralized infrastructure that places storage and processing components at the edge of the cloud, where data sources such as application users and sensors exist.It is an architecture that uses edge devices to carry out a substantial amount of computation (edge computing), storage, and communication locally and routed over the Internet backbone.To achieve real-time automation, data capture and analysis has to be done in real-time without having to deal with the high latency and low bandwidth issues that occur during the processing of network data In 2012, Cisco introduced the term fog computing for dispersed cloud infrastructures.. In 2015, Cisco partnered with Microsoft, Dell, Intel, Arm and Princeton University to form the OpenFog Consortium.The consortium's primary goals were to both promote and standardize fog computing. These concepts brought computing resources closer to data sources.Fog computing also differentiates between relevant and irrelevant data. While relevant data is sent to the cloud for storage, irrelevant data is either deleted or transmitted to the appropriate local platform. As such, edge computing and fog computing work in unison to minimize latency and maximize the efficiency associated with cloud-enabled enterprise systemsFog computing consists of various componets such as fog nodes.Fog nodes are independent devices that pick up the generated information. Fog nodes fall under three categories: fog devices, fog servers, and gateways. These devices store necessary data while fog servers also compute this data to decide the course of action. Fog devices are usually linked to fog servers. Fog gateways redirect the information between the various fog devices and servers. With Fog computing, local data storage and scrutiny of time-sensitive data become easier. With this the amount and the distance of passing data to the cloud is reduced, therefore reducing the security challenges.Fog computing enables data processing based on application demands, available networking and computing resources. This reduces the amount of data required to be transferred to the cloud, ultimately saving network bandwidth.Fog computing can run independently and ensure uninterrupted services even with fluctuating network connectivity to the cloud. It performs all time-sensitive actions close to end users which meets latency constraints of IoT applications.
IoT applications where data is generated in terabytes or more, where a quick and large amount of data processing is required and sending data to the cloud back and forth is not feasible, are good candidates for fog computing. Fog computing provides real-time processing and event responses which are critical in healthcare. Besides, it also addresses issues regarding network connectivity and traffic required for remote storage, processing and medical record retrieval from the cloud.
Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks.
All the details of Fog Computing is discussed in this PPT, its better to get knowledge about this ppt,All the details of applications and examples are covered..
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider. For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network .This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
ABSTRACT
Cloud computing promises to significantly change the way we use computers and access and store our personal and business information. With these new computing and communications paradigms arise new data security challenges. Existing data protection mechanisms such as encryption have failed in preventing data theft attacks, especially those perpetrated by an insider to the cloud provider.
For securing user data from such attacks a new paradigm called fog computing can be used. Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined network This technique can monitor the user activity to identify the legitimacy and prevent from any unauthorized user access. Here we have discussed this paradigm for preventing misuse of user data and securing information.
CONCLUSION
This proposal of monitoring data access patterns by profiling user behavior to determine if and when a malicious insider illegitimately accesses someone’s documents in a Cloud service. Decoy documents stored in the Cloud alongside the user’s real data also serve as sensors to detect illegitimate access. Once unauthorized data access or exposure is suspected, and later verified, with challenge questions for instance, this inundate the malicious insider with bogus information in order to dilute the user’s real data. Such preventive attacks that rely on disinformation technology could provide unprecedented levels of security in the Cloud and in social networks.
Fog computing is defined as a decentralized infrastructure that places storage and processing components at the edge of the cloud, where data sources such as application users and sensors exist.It is an architecture that uses edge devices to carry out a substantial amount of computation (edge computing), storage, and communication locally and routed over the Internet backbone.To achieve real-time automation, data capture and analysis has to be done in real-time without having to deal with the high latency and low bandwidth issues that occur during the processing of network data In 2012, Cisco introduced the term fog computing for dispersed cloud infrastructures.. In 2015, Cisco partnered with Microsoft, Dell, Intel, Arm and Princeton University to form the OpenFog Consortium.The consortium's primary goals were to both promote and standardize fog computing. These concepts brought computing resources closer to data sources.Fog computing also differentiates between relevant and irrelevant data. While relevant data is sent to the cloud for storage, irrelevant data is either deleted or transmitted to the appropriate local platform. As such, edge computing and fog computing work in unison to minimize latency and maximize the efficiency associated with cloud-enabled enterprise systemsFog computing consists of various componets such as fog nodes.Fog nodes are independent devices that pick up the generated information. Fog nodes fall under three categories: fog devices, fog servers, and gateways. These devices store necessary data while fog servers also compute this data to decide the course of action. Fog devices are usually linked to fog servers. Fog gateways redirect the information between the various fog devices and servers. With Fog computing, local data storage and scrutiny of time-sensitive data become easier. With this the amount and the distance of passing data to the cloud is reduced, therefore reducing the security challenges.Fog computing enables data processing based on application demands, available networking and computing resources. This reduces the amount of data required to be transferred to the cloud, ultimately saving network bandwidth.Fog computing can run independently and ensure uninterrupted services even with fluctuating network connectivity to the cloud. It performs all time-sensitive actions close to end users which meets latency constraints of IoT applications.
IoT applications where data is generated in terabytes or more, where a quick and large amount of data processing is required and sending data to the cloud back and forth is not feasible, are good candidates for fog computing. Fog computing provides real-time processing and event responses which are critical in healthcare. Besides, it also addresses issues regarding network connectivity and traffic required for remote storage, processing and medical record retrieval from the cloud.
Fog Computing is a paradigm that extends Cloud computing and services to the edge of the network. Similar to Cloud, Fog provides data, compute, storage, and application services to end-users. The motivation of Fog computing lies in a series of real scenarios, such as Smart Grid, smart traffic lights in vehicular networks and software defined networks.
All the details of Fog Computing is discussed in this PPT, its better to get knowledge about this ppt,All the details of applications and examples are covered..
Security and Privacy Issues of Fog Computing: A SurveyHarshitParkar6677
Abstract. Fog computing is a promising computing paradigm that ex-
tends cloud computing to the edge of networks. Similar to cloud comput-
ing but with distinct characteristics, fog computing faces new security
and privacy challenges besides those inherited from cloud computing. In
this paper, we have surveyed these challenges and corresponding solu-
tions in a brief manner.
Efficient ECC-Based Authentication Scheme for Fog-Based IoT EnvironmentIJCNCJournal
The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
Efficient ECC-Based Authentication Scheme for Fog-Based IoT EnvironmentIJCNCJournal
The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
Cloud computing is a distributed computing system that offers managed, scalable and secured and high available computation resources and software as a service. Mobile computing is the combination of the heterogeneous domains like Mobile computing, Cloud computing & wireless networks.This paper mainly discusses the literature review on Cloud and the Mobile cloud computing. Here in this paper we analyse existing security challenges and issues involved in the cloud computing and Mobile cloud environment. This paper identifies key issues, which are believed to have long-term significance in cloud computing & mobile cloud security and privacy, based on documented problems and exhibited weaknesses.
BIOMETRIC SMARTCARD AUTHENTICATION FOR FOG COMPUTINGIJNSA Journal
In the IoT scenario, things at the edge can create significantly large amounts of data. Fog Computing has recently emerged as the paradigm to address the needs of edge computing in the Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications. In a Fog Computing environment, much of the processing would take place closer to the edge in a router device, rather than having to be transmitted to the Fog. Authentication is an important issue for the security of fog computing since services are offered to massive-scale end users by front fog nodes.Fog computing faces new security and privacy challenges besides those inherited from cloud computing. Authentication helps to ensure and confirms a user's identity. The existing traditional password authentication does not provide enough security for the data and there have been instances when the password-based authentication has been manipulated to gain access into the data. Since the conventional methods such as passwords do not serve the purpose of data security, research worksare focused on biometric user authentication in fog computing environment. In this paper, we present biometric smartcard authentication to protect the fog computing environment.
BIOMETRIC SMARTCARD AUTHENTICATION FOR FOG COMPUTINGIJNSA Journal
In the IoT scenario, things at the edge can create significantly large amounts of data. Fog Computing has recently emerged as the paradigm to address the needs of edge computing in the Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications. In a Fog Computing environment, much of the processing would take place closer to the edge in a router device, rather than having to be transmitted to the Fog. Authentication is an important issue for the security of fog computing since services are offered to massive-scale end users by front fog nodes.Fog computing faces new security and privacy challenges besides those inherited from cloud computing. Authentication helps to ensure and confirms a user's identity. The existing traditional password authentication does not provide enough security for the data and there have been instances when the password-based authentication has been manipulated to gain access into the data. Since the conventional methods such as passwords do not serve the purpose of data security, research worksare focused on biometric user authentication in fog computing environment. In this paper, we present biometric smartcard authentication to protect the fog computing environment.
Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the internet backbone.
Security and Privacy Issues of Fog Computing: A SurveyHarshitParkar6677
Abstract. Fog computing is a promising computing paradigm that ex-
tends cloud computing to the edge of networks. Similar to cloud comput-
ing but with distinct characteristics, fog computing faces new security
and privacy challenges besides those inherited from cloud computing. In
this paper, we have surveyed these challenges and corresponding solu-
tions in a brief manner.
Efficient ECC-Based Authentication Scheme for Fog-Based IoT EnvironmentIJCNCJournal
The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
Efficient ECC-Based Authentication Scheme for Fog-Based IoT EnvironmentIJCNCJournal
The rapid growth of cloud computing and Internet of Things (IoT) applications faces several threats, such as latency, security, network failure, and performance. These issues are solved with the development of fog computing, which brings storage and computation closer to IoT-devices. However, there are several challenges faced by security designers, engineers, and researchers to secure this environment. To ensure the confidentiality of data that passes between the connected devices, digital signature protocols have been applied to the authentication of identities and messages. However, in the traditional method, a user's private key is directly stored on IoTs, so the private key may be disclosed under various malicious attacks. Furthermore, these methods require a lot of energy, which drains the resources of IoT-devices. A signature scheme based on the elliptic curve digital signature algorithm (ECDSA) is proposed in this paper to improve the security of the private key and the time taken for key-pair generation. ECDSA security is based on the intractability of the Elliptic Curve Discrete Logarithm Problem (ECDLP), which allows one to use much smaller groups. Smaller group sizes directly translate into shorter signatures, which is a crucial feature in settings where communication bandwidth is limited, or data transfer consumes a large amount of energy. In this paper, we have chosen the safe curve types of elliptic-curve cryptography (ECC) such as M221, SECP256r1, curve 25519, Brainpool P256t1, and M-551. These types of curves are the most secure curves of other curves of ECC as their security is based on the complexity of the ECDLP of the curve. And these types of curves exceed the complexity of the ECDLP. A valid signature can be generated without reestablishing the whole private key. ECDSA ensures data security and successfully reduces intermediate attacks. The efficiency and effectiveness of ECDSA in the IoT environment are validated by experimental evaluation and comparison analysis. The results indicate that, in comparison to the two-party ECDSA and RSA, the proposed ECDSA decreases computation time by 65% and 87%, respectively. Additionally, as compared to two-party ECDSA and RSA, respectively, it reduces energy consumption by 77% and 82%.
Cloud computing is a distributed computing system that offers managed, scalable and secured and high available computation resources and software as a service. Mobile computing is the combination of the heterogeneous domains like Mobile computing, Cloud computing & wireless networks.This paper mainly discusses the literature review on Cloud and the Mobile cloud computing. Here in this paper we analyse existing security challenges and issues involved in the cloud computing and Mobile cloud environment. This paper identifies key issues, which are believed to have long-term significance in cloud computing & mobile cloud security and privacy, based on documented problems and exhibited weaknesses.
BIOMETRIC SMARTCARD AUTHENTICATION FOR FOG COMPUTINGIJNSA Journal
In the IoT scenario, things at the edge can create significantly large amounts of data. Fog Computing has recently emerged as the paradigm to address the needs of edge computing in the Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications. In a Fog Computing environment, much of the processing would take place closer to the edge in a router device, rather than having to be transmitted to the Fog. Authentication is an important issue for the security of fog computing since services are offered to massive-scale end users by front fog nodes.Fog computing faces new security and privacy challenges besides those inherited from cloud computing. Authentication helps to ensure and confirms a user's identity. The existing traditional password authentication does not provide enough security for the data and there have been instances when the password-based authentication has been manipulated to gain access into the data. Since the conventional methods such as passwords do not serve the purpose of data security, research worksare focused on biometric user authentication in fog computing environment. In this paper, we present biometric smartcard authentication to protect the fog computing environment.
BIOMETRIC SMARTCARD AUTHENTICATION FOR FOG COMPUTINGIJNSA Journal
In the IoT scenario, things at the edge can create significantly large amounts of data. Fog Computing has recently emerged as the paradigm to address the needs of edge computing in the Internet of Things (IoT) and Industrial Internet of Things (IIoT) applications. In a Fog Computing environment, much of the processing would take place closer to the edge in a router device, rather than having to be transmitted to the Fog. Authentication is an important issue for the security of fog computing since services are offered to massive-scale end users by front fog nodes.Fog computing faces new security and privacy challenges besides those inherited from cloud computing. Authentication helps to ensure and confirms a user's identity. The existing traditional password authentication does not provide enough security for the data and there have been instances when the password-based authentication has been manipulated to gain access into the data. Since the conventional methods such as passwords do not serve the purpose of data security, research worksare focused on biometric user authentication in fog computing environment. In this paper, we present biometric smartcard authentication to protect the fog computing environment.
Fog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation, storage, and communication locally and routed over the internet backbone.
Similar to seminarpptfogcomp-170420185314.pptx (20)
1. Jain College of Engineering
T.S Nagar, Machhe, Belagavi-590014
Seminar on
“FOG COMPUTING”
Submitted By
MAHANTESH HIREMATH
(2JI13CS024)
Under the Guidance of
PROF. VIJAYALAXMI S. NAGANUR
Department of Computer science and Engineering
2016-2017
4. What Is FOG Computing.
Fog Computing is a technology that extends cloud computing and services
to the edge of the network.
It provides data, compute, storage and application services to the users like
cloud.
Fog computing is an emerging technology that is basically used for Internet
of Things.
6. Asimple three level hierarchy as shown in above Figure.
In this framework, each smart thing is attached to one of Fog devices.
Fog devices could be interconnected and each of them is linked to the
Cloud.
As Fog computing is implemented at the edge of the network, it
provides low latency, location awareness, and improves quality-of-
services (QoS) for streaming and real time applications.
7. EXISTING SYSTEM
Cloud computing has provided many opportunities for enterprises by
offering their customers a range of computing services. Current “pay-as-
you-go” Cloud computing model becomes an efficient alternative to owning
and managing private data centers for customers facing Web applications
8. DISADVANTAGES
Existing data protection mechanisms such as encryption was failed in
securing the data from the attackers.
It does not verify whether the user was authorized or not.
Cloud computing security does not focus on ways of secure the data from
unauthorized access.
9. PROPOSED SYSTEM
Unlike traditional data centers, Fog
are geographically
over heterogeneous
devices
distributed
platforms,
management
interested in
spanning
domains.
innovative
multiple
Cisco is
proposals
that facilitate service mobility across
platforms, and technologies that
preserve end-user and content
security and privacy across domains.
10. ADVANTAGES
Fog can be distinguished from Cloud by its proximity to end-users.
The dense geographical distribution and its support for mobility.
It provides low latency, location awareness, and improves quality-of-
services (QoS) and real time applications.
12. User behavior profiling
• User profiling is a well-known technique that can be applied here to model
how, when, and how much a user accesses their information in the Cloud.
• Simple user specific features can serve to detect abnormal Cloud access based
partially upon the scale and scope of data transferred.
• Behaviour based security: a ‘normal user’ behaviour can be continuously
checked to determine whether abnormal access to a user’s information is
occurring.
Ex: Fraud detection applications.
13. Decoy system
Decoy data, such as decoy documents, honey
pots and other bogus information can be
generated on demand and used for detecting
unauthorized access to information and to
poison the thief’s ex-filtrated information.
Serving decoys will confuse an attacker into
believing they have ex-filtrated useful
information, when they have actually not.
14. Fog computing architecture
ADMIN
ADMIN
OPERATIONS
ANSWER TO
QUESTIONS
LOGIN
USER
LOGIN
SIGN UP
ANSWER TO
QUESTIONS
ENTER
USERNAME
ENTER
PASSWORD
VIEW MY
FILES
SEND
MAIL
DOWNLOAD
FILES
UPLOAD
FILES
ORIGINAL
DOCUMENT
DECOY
DOCUMENT
FOG COMPUTING
15. APPLICATIONS OF FOG
• Connected cars: Fog computing is ideal for Connected Vehicles (CV)
because real-time interactions will make communications between cars,
access points and traffic lights as safe and efficient as possible
16. • Smart grids: Fog computing allows fast, machine-to-machine (M2M)
handshakes and human to machine interactions (HMI), which would work
in cooperation with the cloud
Fig. Fog computing in smart grid
17. SECURITY ISSUES
The main security issues are authentication at different
levels of gateways as well as (in case of smart grids) at the smart meters
installed in the consumer’s home. Each smart meter and smart appliance
has an IP address. A malicious user can either tamper with its own smart
meter, report false readings, or spoof IP addresses.
18. EXAMPLE : MAN-IN –MIDDLE-ATTACK
In this subsection, we take man- in-the-middle attack as
an example to expose the security problems in Fog computing. In this
attack, gateways serving as Fog devices may be compromised or replaced by
fake ones .
19. PRIVACY ISSUES
In smart grids, privacy issues deal with hiding details, such as what
appliance was used at what time, while allowing correct summary
information for accurate charging.
20. CONCLUSION
With the increase of data theft attacks the security of user data is becoming
a serious issue for cloud service providers for which Fog Computing is a
paradigm which helps in monitoring the behavior of the user and providing
security to the user’s data. By using decoy technique in Fog can minimize
insider attacks in cloud. Fog provides unprecedented levels of security in the
Cloud and in social networks. The usage of fog computing can accelerate
the innovation process in ways that has never been seen before.
21. REFERENCES
1F. Bonomi, “Connected vehicles, the internet of things, and fog com- puting,”
in The Eighth ACM International Workshop on Vehicular Inter- Networking
(VANET), Las Vegas, USA, 2011.
2F. Bonomi, R. Milito, J. Zhu, and S. Addepalli, “Fog computing and its role
in the internet of things,” in Proceedings of the First Edition of the MCC
Workshop on Mobile Cloud Computing, ser. MCC’12. ACM,2012, pp. 13–16.