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Efficient Approaches for Improving the Performance Metrics of Wireless Intrusion System

by P. C. Kishoreraja, D. Dhanasekaran, Christeena.j
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 57 - Number 3
Year of Publication: 2012
Authors: P. C. Kishoreraja, D. Dhanasekaran, Christeena.j
10.5120/9095-3141

P. C. Kishoreraja, D. Dhanasekaran, Christeena.j . Efficient Approaches for Improving the Performance Metrics of Wireless Intrusion System. International Journal of Computer Applications. 57, 3 ( November 2012), 19-27. DOI=10.5120/9095-3141

@article{ 10.5120/9095-3141,
author = { P. C. Kishoreraja, D. Dhanasekaran, Christeena.j },
title = { Efficient Approaches for Improving the Performance Metrics of Wireless Intrusion System },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 57 },
number = { 3 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 19-27 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume57/number3/9095-3141/ },
doi = { 10.5120/9095-3141 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:59:29.972367+05:30
%A P. C. Kishoreraja
%A D. Dhanasekaran
%A Christeena.j
%T Efficient Approaches for Improving the Performance Metrics of Wireless Intrusion System
%J International Journal of Computer Applications
%@ 0975-8887
%V 57
%N 3
%P 19-27
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Security has become one of the major problems that wireless ad-hoc networks face today. With considering limited energy resources and specific attack detection, this paper focus on wireless node behavior based anomaly intrusion detection system and deals only with MAC features and network features behavior of wireless node. This paper also introduces two types of feature set and behavioral indices. The detection uses threshold technique for behavioral indices. The performance has been evaluated for MAC and network layer feature set of wireless nodes.

References
  1. Amitabh Mishra, Ketan Nadkarni, and Animesh Patcha (2004), 'Intrusion Detection in Wireless Ad-hoc Networks', IEEE Wireless Communication Magazine, pp 48-67.
  2. Anantvalee T. and Wu J. (2006), 'A Survey on Intrusion Detection in Mobile Ad-hoc Networks', Wireless/Mobile Network Security, Springer, pp. 170-196.
  3. Balachandran S. ,Dasgupta D. and Wang L. (2006), 'A Hybrid Approach for Misbehavior Detection in Wireless Ad-Hoc Networks', Proceedings of the Symposium on Information Assurance,Manchester,UK.
  4. Caleb Phillips and Suresh Singh (2007), 'Analysis of WLAN traffic in the wild', proceedings of IFIP Networking 2007, Altanta.
  5. Crosbie M. and Spafford G. (1995), 'Applying genetic programming to intrusion detection', Proceedings of the AAAI Fall Symposium on Genetic Programming, Stanford, California, pp. 1-8.
  6. Darrell Whitney (1993), ' A Genetic Algorithm Tutorial', Technical Report CS-93-103 ( Revised) , Department of Computer Science , Colorado State University.
  7. Heywood M. I. , Zincir-Heywood A. N (2002), 'Dynamic page based crossover in linear genetic programming', IEEE Transactions on Systems, Man, and Cybernetics: Part B – Cybernetics, 32(3),pp-380–388.
  8. Huang Y. , Fan W. , Lee W. and Yu P. S. (2003), 'Cross-Feature Analysis for Detecting Ad-hoc Routing Anomalies', Proceedings of the 23rd International Conference on Distributed Computing Systems, Providence, pp. 478-487.
  9. Jim Parker ,Anand Patwardhan, and Anupam Joshi (2006), 'Detecting Wireless Misbehaviour through Cross-layer Analysis', Proceedings of the IEEE Consumer Communications and Networking Conference Special Sessions,Nevada,USA.
  10. Laroche P. and Zincir-Heywood A. N. (2006), '802. 11 De-authentication Attack Detection Using Genetic Programming', Proceedings of the 9th European Conference on Genetic Programming, Hungary.
  11. Laroche P. and Zincir-Heywood A. N. (2006), 'Genetic Programming Based WiFi Data Link Layer Attack Detection', Proceedings of the IEEE CNSR 2006, Canada.
  12. Liu Y. and Man H. (2005), 'MAC layer anomaly detection in ad-hoc networks', Proceedings of the sixth IEEE Systems, Man and Cybernetics Information Assurance Workshop, West Point, pp. 402-409.
  13. Marti S. ,Giuli T. J. ,Lai K. and Baker M. (2000), 'Mitigating routing misbehaviour in mobile ad-hoc networks', Proceedings of ACM MOBICOM, Boston, pp. 255-265.
  14. Matthew V. Mahoney and Philip K. Chan (2006), 'Learning Models of Network Traffic for Detecting Novel Attacks', Technical Report, Florida Institute of Technology.
  15. Patrick LaRoche and Nur Zincir-Heywood A. (2005), '802. 11 Network Intrusion Detection using Genetic Programming', Genetic and Evolutionary Computation Conference workshop program, Las Vegas, pp. 170-171.
  16. Raghavan S V and Swami Nathan N (2000), 'Intelligent Prefetch in WWW Using Client Behavior Characterization', International Conference on Web Technologies, San Francisco.
  17. Raghavan S. V. and Balajinath B. (2001), 'Intrusion Detection Through Learning Behavior Model', International Journal Of Computer Communications, Vol 24, No 12, pp. 1202-1212.
  18. Song D. , Heywood M. I. , and Zincir-Heywood A. N. (2005), 'Training genetic programming on half a million patterns: an example from anomaly detection', IEEE Transactions on Evolutionary Computation, 9(3):225–239.
  19. Tai Hoon Kim and Madhavi S. (2009), 'An Intrusion detection system in mobile ad-hoc networks', International Journal of Security and its applications , Vol. 2,No. 3, pp. 1-16
  20. Wei Wang, Xiaohong Guan and Xiangliang Zhang (2008), 'Processing of Massive Audit Data Streams for Real-Time Anomaly Intrusion Detection', Computer Communications, Elsevier, vol. 31, no. 1, pp. 58-72.
  21. Wenjia Li and Anupam Joshi (2006), 'Security Issues in Mobile Ad-hoc Network-A Survey', Technical Report, Department of Computer Science and Electrical Engineering, University of Maryland, Baltimore County.
  22. Zhang B. and Yan J. (2007), 'Document transformation for multi-label feature selection in text categorization', Proceedings of Seventh IEEE International Conference on Data Mining,USA, pp. 451-456.
Index Terms

Computer Science
Information Sciences

Keywords

Anomaly intrusion detection genetic algorithm MAC layer and Network layer

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