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Behavior Based Anomaly Detection Technique to Mitigate the Routing Misbehavior in MANET
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International Journal of Computer Science and Security (IJCSS)
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Volume:  3    Issue:  2
Pages:  62-153
Publication Date:   April 2009
ISSN (Online): 1985-1553
62 - 75
Published Date   
CSC Journals, Kuala Lumpur, Malaysia
Keywords   Abstract   References   Cited by   Related Articles   Collaborative Colleague
KEYWORDS:   intrusion detection, anomaly detection, mobile ad hoc network, security 
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Mobile ad hoc network does not have traffic concentration points such as gateway or access points which perform behavior monitoring of individual nodes. Therefore, maintaining the network function for normal nodes when other nodes do not route and forward correctly is a big challenge. This paper, address the behavior based anomaly detection technique inspired by the biological immune system to enhance the performance of MANET to operate despite the presence of misbehaving nodes. Due to its reliance on overhearing, the existing watchdog technique may fail to detect misbehavior or raise false alarms in the presence of ambiguous collisions, receiver collisions, and limited transmission power. Our proposed scheme uses intelligent machine learning techniques that learns and detects each node by false alarm and negative selection approach. We consider DSR, AODV and DSDV [24],[25] as underlying routing protocol which are highly vulnerable to routing misbehavior. Analytical and simulation results are presented to evaluate the performance of the proposed scheme. Keywords: intrusion detection, anomaly detection, mobile ad hoc network, security.  
1 C.Perkins and P.Bhagwat, “Highly dynamic destination-sequenced distance-vector routing (DSDV) for mobile computers,” in proceedings of the ACM SIGCOMM’94 Conference on Communications Architectures, Protocol and Applications, London, UK, August 1994, pp.234- 244.
2 L. Buttyan and J.-P. Hubaux, “Security and Cooperation in Wireless Networks,”, 2006.
3 L.M. Feeney and M. Nilsson, “Investigating the Energy Consumption of a Wireless Network Interface in an Ad Hoc Networking Environment,” Proc. IEEE INFOCOM, 2001.
4 L. Zhou and Z.J. Haas, “Securing Ad Hoc Networks,” IEEE Network Magazine, vol. 13, no. 6, Nov./Dec. 1999.
5 F. Stajano and R. Anderson, “The Resurrecting Duckling: Security Issues in Ad-Hoc Wireless Networks,” Proc. Seventh Int’l Workshop Security Protocols, 1999.
6 J. Kong, P. Zerfos, H. Luo, S. Lu, and L. Zhang, “Providing Robust and Ubiquitous Security Support for Mobile Ad-Hoc Networks,” Proc. IEEE Int’l Conf. Network Protocols (ICNP ’01), 2001.
7 I. Aad, J.-P. Hubaux, and E-W. Knightly, “Denial of Service Resilience in Ad Hoc Networks,” Proc. MobiCom, 2004.
8 L. Buttyan and J.-P. Hubaux, “Enforcing Service Availability in Mobile Ad-Hoc WANs,” Proc. MobiHoc, Aug. 2000.
9 J.-P. Hubaux, T. Gross, J.-Y. LeBoudec, and M. Vetterli, “Toward Self-Organized Mobile Ad Hoc Networks: The Terminodes Project,” IEEE Comm. Magazine, Jan. 2001.
10 L. Buttyan and J.-P. Hubaux, “Stimulating Cooperation in Self-Organizing Mobile Ad Hoc Networks,” ACM/Kluwer Mobile Networks and Applications, vol. 8, no. 5, 2003.
11 S. Zhong, J. Chen, and Y.R. Yang, “Sprite: A Simple, Cheat-Proof,Credit-Based System for Mobile Ad-Hoc Networks,” Proc. INFOCOM, Mar.-Apr. 2003.
12 S. Marti, T. Giuli, K. Lai, and M. Baker, “Mitigating Routing Misbehavior in Mobile Ad Hoc Networks,” Proc. MobiCom, Aug.2000.
13 S. Buchegger and J.-Y. Le Boudec, “Performance Analysis of the CONFIDANT Protocol: Cooperation of Nodes, Fairness in Dynamic Ad-Hoc Networks,” Proc. MobiHoc, June 2002.
14 Y. Lim, T. Schmoyer, J. Levine and H. L. Owen. “ Wireless Intrusion Detection and Response”. In Proceedings of the 2003 IEEE workshop on Information Assurance United States Military Academy, NY: West Point.
15 Y. Zhang and W. Lee. Au gust 6-11, 2000. “Intrusion Detection in Wireless Ad-Hoc Networks”. In Proceedings of the Sixth Annual International Conference on Mobile Computing and Networking, Boston: Massachusetts.
16 S. Balachand ran, D. Dasgupta, F. Nino, D. Garrett, “ Framework for Evolving Multi- Shaped Detectors in Negative Selection”. Submitted to the IEEE Transactions on Evolutionary Computation, January 2006.
17 D. Dasgupta and D. R McGregor, “ sGA: A structured Genetic Algorithm”. Research Report IKBS-11-93, April 1993.
18 F. González, “A study of Artificial Immune Systems Applied to Anomaly Detection”, . PhD. Dissertation, Advisor: Dr. Dipankar Dasgupta, The University of Memphis, May 2003.
19 M. Kaniganti. “An Agent-Based Intrusion Detection System for Wireless LANs”, Masters Thesis, Advisor: Dr. Dipankar Dasgupta. The University of Memphis, December 2003.
20 S. Sarafijanovic and J.Y. Le Boudec. “An Artificial Immune System for Misbehavior Detection in Mobile Ad-Hoc Networks with Virtual Thymus, Clustering, Danger Signal and Memory Detectors”. In Proceedings of ICARIS-2004 (Third International Conference on Artificial Immune Systems), pp . 342-356, Septemb er 13-16, 2004, Catania, Italy
21 J. Kim and P.J. Bentley. “The Artificial Immune Model for Network Intrusion Detection”, 7th European Conference on Intelligent Techniques and Soft Computing (EUFIT’99), Aachen, Germany.
22 Scalable Network Technologies, “Qualnet simulator-version 4.5,” Software package 2008,[online]. Available :
23 H. Miranda and L. Rodrigues, “Preventing Selfishness in Open Mobile Ad Hoc Networks,” Proc. Seventh CaberNet Radicals Workshop, Oct. 2002.
24 Meera Gandhi, S.K.Srivatsa,” Detecting and preventing attacks using network intrusion detection systems”, in the International Journal of Computer Science and Security, Volume: 2, Issue: 1, Pages: 49-58.
25 N.Bhalaji, A.Shanmugam, Druhin mukherjee, Nabamalika banerjee.” Direct trust estimated on demand protocol for secured routing in mobile Adhoc networks”, in the International Journal of Computer Science and Security, Volume: 2, Issue: 5, Pages: 6-12.
1 K. P. David, “Decentralised Soft-Security in Distributed Systems”, Ph.D. Thesis, College of Engineering and Physical Sciences, University of Birmingham., 2011.
2 G. S. Mamatha and S. C. Sharma, “A Robust Approach to Detect and Prevent Network Layer Attacks in MANETS”, International Journal of Computer Science and Security (IJCSS), 4(3), pp. 275 – 284, 2010.
1 TechRepublic
3 ZDNet
Sundararajan Paramasivam Tharai Vinay : Colleagues
A.Shanmugam : Colleagues  
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