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Eliminating Gray Holes in Mobile Ad hoc Network Discovering a Secure Path

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Eliminating Gray Holes in Mobile Ad hoc Network Discovering a Secure Path by Threshold MechanismABSTRACT Problem Statement: In this thesis firstly we study the effects of Black hole attack in MANET using both Proactive and Reactive routing protocols and then discovering a Secure Path in MANET by Avoiding Black/Gray Holes. Thesis Aims and Objective ▪ This study focus on analysis of black hole attack in MANET and its consequences. Analyzing the effects of black hole attack in the light of throughput and endtoend delay in MANET. ▪ Simulating the black hole attack using Proactive and Reactive routing protocols. ▪ Comparing the results of both Proactive and Reactive protocols to analyze which of these two types of protocols are more vulnerable to Black Hole attack. ▪ Then Discovering a Secure Path in MANET by Avoiding Black/Gray Holes.MANET The term MANET(Mobile Ad hoc Network)refers to a multihop packet based wireless network composed of a set of mobile nodes that can communicate and move at the same time, without using any kind of fixed wired infrastructure.Characteristics of an Adhoc Network Collection of mobile nodes forming a temporary network – Network topology changes frequently and unpredictably – No centralized administration or standard support services – Number of nodes 10 to 100 or at most 1000Black hole Attack ▪ In this type of attacks, malicious node claims having an optimum route to the node whose packets it wants to intercept. On receiving the request the malicious node sends a fake reply with extremely short route . ▪ Once the node has been able to place itself between the communicating nodes, it is able to do anything with the packets passing between them.Gray Hole Attack  A grey hole attack (GH) is a special case of the BH attack, in which an intruder first captures the routes, i.e. becomes part of the routes in the network (as with the BH attack), and then drops packets selectively. For example, the intruder may drop packets from specific source nodes, or it may drop packets probabilistically or drop packets in some other specific pattern.  BH and GH attacks on the other hand comprise two tasks:  The attacker first captures routes and then either drops all packets (BH attack)  or some packets (GH attackProposed Algorithm Notations SN : Source Node DN : Destination Node IN : Intermediate Node TH : Threshold DSeq : Destination Sequence Number Seq : Sequence Number 1. SN broadcasts RREQ to all Nodes 2. IN receives RREQ and forwards until reach DN 3. DN receives RREQ from SN or IN 4. DN gets Seq from RREQ and verifies with Seq in its routing table 5. If Seq of RREQ is greater than Seq of its routing table 6. DN selects Seq of RREQ and plus one 7. Else 8. DN selects Seq of its routing table and plus one9. End if 10. If Seq is greater than or equal TH 11. Seq = 0 12. Else 13. Seq = Seq 14. End if 15. DN generates RREP by using Seq as DSeq and sends back to SN 16. If SN receives RREP for RREQ 17. SN checks the RREP message for Dseq 18. If DSeq is greater than TH 19. Discard this message 20. Else 21. Route is established 22. End if 23. End IfLiterature Review  Lu et al. 3 proposed the SAODV black hole detection scheme for MANETs that is designed to address some of the security weaknesses of AODV and withstand black hole attacks.  Deswal and Singh 4 created an enhanced version of the SAODV protocol that includes password security for each of the routing nodes and routing tables that are updated based on timeliness.  Ramaswamy et al. 5 proposed a method for identifying multiple black hole nodes. They were the first to propose a solution for cooperative black hole attacks. They modified the AODV protocol slightly by introducing a Data Routing Information (DRI) table and a cross checking mechanism. Each entry of the node is maintained by the table. This method uses the reliable nodes to transfer the packetsSimulation Tool Used  This Dissertation work using OPNET Modeler16.0 Network Simulator.  OPNET Modeler16.0 is a Commercial Network Simulator.  Designed for modelling communication devices, technologies, and protocols and to simulate the performance of these technologies. Figure : OPNET 16.0 Scenarios Name No. of Mobile Nodes Protocol Used Scenarios Normal Network 100 AODV Under Gray Hole 100 AODV Used Attack Mitigation of Gray 100 AODV Hole Attack Normal Network 150 AODV Under Gray Hole 150 AODV Attack Mitigation of Gray 150 AODV Hole Attack Table1: Scenario UsedExamined Protocols Cases AODV with and without Gray Hole Attack Number of Nodes 100 and 150 Simulation Types of Nodes Vehicular Simulation Area 5555 km Statistics Simulation Time 1800 seconds Mobility Uniform(50100) m/s Pause Time 100 seconds Performance Parameters Throughput, Delay, Network load No. of Gray Hole Node 10 Trajectory VECTOR Data Type Constant Bit Rate (CBR) Packet Size 1024 bytes Traffic type FTP, Http Active Route Timeout(sec) 3 Hello interval(sec) 1,2 Hello Loss 3 Timeout Buffer 2 Physical Characteristics Extended rate IEEE 802.11g (OFDM) Data Rates(bps) 54 MbpsContinued… Transmit Power 0.005 RTS Threshold 1024 PacketReception Threshold 95 Performance Parameters Throughput, Delay, Network load Trajectory VECTOR Long Retry Limit 4 Max Receive Lifetime (seconds) 0.5 Buffer Size(bits) 25600Scenario of Without Gray HoleScenario of With Gray HoleRESULTSThroughput  Throughput is one of the more important and common network performance metrics. Measured in bits/sec or in packets/sec, it represents the amount of bits or packets that are successfully transferred over a link.  High throughput values indicate efficient network function as packets sent reach their destination without being dropped and retransmitted for various reasons.  In first scenario of our experimentation, packets travels are shown as throughput with peak value of approx. 268678 and it is represented as bits per second.  In second scenario which is with gray hole attack, packets drops which are represented as throughput, decreases to value of approx. 188933 bits per second.▪ Throughputs of all three scenarios at 100 nodesThroughput of all three scenarios at 150 nodesEndtoEnd Delay  Endtoend delay is the average time that starts in the first node by generating the packets till the arriving the packets in destination node which shown in seconds.  In first scenario of 100 nodes of our experimentation, packets Delay are shown as figure with peak value of approx. 0.459 seconds.  In second scenario which is with gray hole attack, packets delay Increases to value of approx 0.00030 seconds.  In first scenario of 150 nodes of our experimentation, packets delay are approx. 0.001 seconds.  In second scenario which is with gray hole attack, packets delay increases to value of approx. 0.25 seconds. Delay of all three scenarios at 100 nodesDelay of all three scenarios at 150 nodesConclusion  With the importance of Wireless Mesh Networks (WMN) comparative to its vast potential it has still many challenges left in order to overcome. Security of WMN is one of the important features for its deployment.  The main concern of this work to show the performance of AODV under normal surroundings, under gray hole attack and performance after elimination of gray hole attack in term of End to End delay and throughput.  The network performance with gray hole attack in term of throughput decreases around 188933 bits per second. By our proposed approach, we have recovered around 234544 in throughput.  The network performance with gray hole attack in term of end to end delay increases around 54 and with our proposed approach, we have recovered around 45 in delay.Reference 1 Fatima Ameza, Nassima Assam and Rachid Beghdad,“Defending AODV Routing Protocol Against the Black HoleAttack”, International Journal of Computer Science and Information Security, Vol. 8, No.2, 2010, pp.112117. 2 Nital Mistry, Devesh C. Jinwala and Mukesh Zaveri,“Improving AODV Protocol against Blackhole Attacks”, International Multiconference of Engineers and Computer Scientists 2010, vol. 2, March 2010. 3 Payal N. Raj and Prashant B.Swadas,”DPRAODV: A dynamic learning system against black hole attack in AODV based Manet”, International Journal of Computer Science Issues, Vol. 2, Issue 3, 2010, pp: 5459. 4 Hoang Lan Nguyen and Uyen Trang Nguyen,”Study of Different Types of Attacks on Multicast in Mobile Ad HocNetworks”, International Conference on Networking, International Conference on Systems and International Conference on Mobile Communications and Learning Technologies, April 2006, pp. 149149 5 Rutvij H. Jhaveri, Ashish D. Patel, Jatin D. Parmar and Bhavin I. Shah,“MANET Routing Protocols and Wormhole Attack againstAODV”, International Journal of Computer Science and Network Security, vol. 10 No. 4, April 2010, pp. 1218.Continued….. 6 N. Shanthi, Dr. Lganesan and Dr.K.Ramar,“Study of Different Attacks on Multicast Mobile Ad hocNetwork”, Journal of Theoretical and Applied Information Technology, December 2009, pp. 4551. 7 Abhay Kumar Rai, Rajiv Ranjan Tewari and Saurabh Kant Upadhyay ,“Different Types of Attacks on Integrated MANETInternetCommunication”, International Journal of Computer Science and Security, vol. 4 issue 3, July 2010, pp. 265274. 8 Jakob Eriksson, Srikanth V. Krishnamurthy, Michalis Faloutsos,“TrueLink: A Practical Countermeasure to the Wormhole Attack in WirelessNetworks”, 14th IEEE International Conference on Network Protocols, November 2006, pp.7584. 9 Mahdi Taheri, Dr. majid naderi, Mohammad Bagher Barekatain,“New Approach for Detection and defending the Wormhole Attacks in Wireless Ad HocNetworks”, 18th Iranian Conference on Electrical Engineering,, May 2010, pp. 331335. 10 Dang Quan Nguyen and Louise Lamont, “A Simple and Efficient Detection of Wormhole Attacks”, New Technologies, Mobility and Security, November 2008, pp. 15.Thanks Any questions You can find us at queriesthesisscientist.com
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