security issues of iot with fog

SECURITY ISSUES OF IOT WITH FOG.

Achu Anna AntonyS1 M.Tech CSE

Roll No: 01Guide: Mr.Bino ThomasAssistant Professor, CSE

November 9, 2016

Achu Anna Antony S1 M.Tech CSE Roll No: 01 Guide: Mr.Bino Thomas Assistant Professor, CSESECURITY ISSUES OF IOT WITH FOG. 1 / 25

OUTLINE

Introduction

Existing System

Problem Statement

Proposed System

Conclusion

Future Works

References


INTRODUCTION

Cloud: Storing and accessing data and programs over theInternet instead of computer’s hard drive.IoT : Everyday objects(IoT nodes) connected throughInternet, allowing them to send and receive dataIoT uses:

Internet : Infrastructure to interconnect IoT nodesCloud: Background supporting infrastructure


INTRODUCTION contd...

Huge network latency and Backend overhead occurs as datato be processed increases in IoT cloud. So IoT uses,

Fog as a solution : ie.. intermediate computing buffer betweenIoT nodes and Cloud

Adoption of IoT fog can cause many security threats, which isexplored throughout


EXISTING SYSTEM

Title:- ”Fog Computing and Its Role in the Internet of Things”(F.Bonomi, R. Milito, J. Zhu, and S. Addepalli)

Proposed:Fog Computing - Extension of cloud computing Features used

Features:Highly virtualized platform

LimitationsMulti fog OS prevents from access of other OS. If there occurany problem on Kernel mode, it does not prevent.

Figure: Fog with computing features


EXISTING SYSTEM contd...

Title:-”The Fog Computing Paradigm: Scenarios and SecurityIssues” (I. Stojmenovic and W. Sheng)

Proposed:Man in the middle attack- Fog devices get replaced by fakeones.

Features:Intrusion Detection method signature, behavioural or anomalybased detection method

LimitationsProtection methods like encryption and decryption of dataconsume large amount of battery on mobile devices.

Figure: Man-In-The-Middle AttackAchu Anna Antony S1 M.Tech CSE Roll No: 01 Guide: Mr.Bino Thomas Assistant Professor, CSESECURITY ISSUES OF IOT WITH FOG. 6 / 25

EXISTING SYSTEM contd...

Title:- Semantics-Aware Android Malware Classification UsingWeighted Contextual API Dependency Graphs (M. Zhang, Y.Duan, H. Yun, and Z.Zhao)

Proposed:Android based malware detection

Features:Uses Signature based approach for detection of malwareGraphs are generated from behaviour graphs and convert it tosignature and stores in database.

LimitationsDetection of malware from unknown or new malware familywill be hectic.

Figure: Android based malware to signature conversion[4]


FOG COMPUTING

Fog computing is an extension of cloud computing paradigm,but is a more highly virtualized platform that providescomputation, storage, and networking services between endIoT devices and back-end cloud servers.

Figure: The hierarchical fog computing architecture


ADVANTAGES AND APPLICATIONS OF FOG

Advantages

Greater business agilityLow latencyGeo distributionLower operating expense

Applications

Geographically distributed applicationsFast mobile applicationsLarge-scale distributed control systems


PROBLEM STATEMENT

As fog infrastructure is prone to many security threats, thereis a need for studying about them deeply so as the methodsdiscussed in the proposed systems is needed to combine whichis examined in the proposed system


RELEVANT SECURITY TECHNOLOGIES

Security technology for IoT network

When client wants to access cloud services, he must gothrough authentication process to ensure confidentiality andsecurity for IoT network.

Authorized users can access cloud with mobile devices.

Protocol is of two phases: Registration and Authentication.

Figure: Authentication as a service


RELEVANT SECURITY TECHNOLOGIES contd...

Security technology for fog node

In fog Computing, much of the information is gathered intofog node.

If a wrong information is spread by exploiting vulnerability is abig problem.

So need dynamic analysis techniques to monitor fog node inreal time

Typically, the performance overhead of dynamic analysis ishigh.



Security technology for IoT node

When some IoT nodes are out of order or provide wronginformation, it can affect people.

Attacker has many chances to compromise various deviceswith sensors.

The attacker is able to predict user behavior and abuse itsinformation.



For IoT nodes, to be truly secure, an IoT node must alsoobtain application layer security.

That means that the node itself, and not just thecommunication channel (i.e. the pipe), should beauthenticated.

In addition to channel authentication, encryption and dataintegrity should be established at the application layer toprotect the data flowing through the pipe.


SECURITY AND PRIVACY ISSUES IN FOGCOMPUTING

Man- in- the middle Attack

In this attack, gateways serving as fog devices may becompromised or replaced by fake ones.Use a strong encryption between the client and the server andnever connect to open WiFi routers directly.Encryption and decryption methods consume large amount ofbattery on mobile device.


SECURITY AND PRIVACY ISSUES IN FOGCOMPUTING contd...

Intrusion Detection

Intrusion detection system analyzes and monitors

i) access control policy, ii) a log file, and iii)user loginformation in order to detect intrusion behavior.

It can be run on network side in order to detect maliciousactivity such as DoS, port scanning.

Intrusion detection techniques have been applied to mitigateattacks such as i) insider attack, ii) flooding attack, iii) portscanning, iv) attacks on VM or hypervisor.



Malicious Fog node problem

In order to provide service to user, fog nodes process datareceived from the IoT devices.

If the workloads is heavy, it is divided into several jobs andprocessed by several fog nodes.

If some fog nodes are compounded by a malicious user, it isdifficult to ensure the integrity of the data.

Before the computation begin, fog nodes must trust eachother.

An authentication protocol is required.



Malicious Detection Technique

When some fog nodes are compromised, hybrid detectiontechnique is useful to detect malicious code in fog nodes.

It is combined with signature-based detection technique andbehavior-based detection technique.



Data Protection

Messages generated from IoT devices is sent to the nearestfog nodes.

When distributed and processed data is merged, the integrityof the data should be guaranteed.

Because of limited resources, it is difficult to encrypt ordecrypt data on IoT device so light-weight encryptionalgorithms or masking techniques are required.



Data Management Issues

Fog nodes are geographically distributed, making it difficult toknow data location.

The user wants to be provided with the same services in otherareas.

It is difficult for user to know whether the node provides thesame service.

Some fog nodes by having duplicated files will cause a wasteof resources.

IoT will create enormous amounts of data there is a need fordistributed intelligence and so-called fast Big Data processing.



Every communication deployment of IoT is unique.

However, there are four basic stages that are common to justabout every IoT application. Those components are:

data collection,data transmission,data assessment, andresponse to the available information.

Successful data management is therefore very important tothe success of IoT.


CONCLUSION

IoT cloud with fog embedded system can overcome

congestion problemnetwork latency

Fog computing provides the improved quality of services tothe user by complementing shortages of IoT cloud.

IoT technology can be utilized in various fields in the future.

This presentation highlights the need to configure the securefog computing environment through security technologies


FUTURE WORKS

Future work should be done to develop a system for efficientlycollect and analyze various logs generated in fog computingenvironment..


REFERENCES

[1] Kanghyo Lee , Donghyun Kim, Dongsoo Ha, Ubaidullah Rajputand Heekuck Oh,”On Security and Privacy Issues of FogComputing supported Internet of Things Environment,”HanyangUniversity, ERICA Campus, South Korea,2015.[2] L.M.Vaquero and L.Rodero-Merino,Finding your Way inFog:Towards a Comprehensive Definition of Fog Computing, ACMSIGCOMM Computer Communication Review, vol.44, Oct. 2014.[3] F.Bonomi, R.Milito, J.Zhu, and S.Addepalli,Fog Computing andIts Role in the Internet of Things, Proceedings of the first editionof the MCC workshop on Mobile Cloud Computing,Aug.2012.[4] I.Stojmenovic and W.Sheng,The Fog Computing Paradigm:Scenarios and Security Issues, Federated Conference on ComputerScience and Information Systems, pp.1-8, Sept. 2014.[5] M.Zhang, Y.Duan, H.Yun, and Z.Zhao,Semantics-AwareAndroid Malware Classification Using Weighted Contextual APIDependency Graphs, Proceedings of the 2014 ACM SIGSACConference on Computer and Communications Security, Nov.2014.


THANK YOU
