CFP last date
20 December 2024
Reseach Article

Article:Distributed and Cooperative Hierarchical Intrusion Detection on MANETs

by Farhan Abdel-Fattah, Zulkhairi Md. Dahalin, Shaidah Jusoh
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 12 - Number 5
Year of Publication: 2010
Authors: Farhan Abdel-Fattah, Zulkhairi Md. Dahalin, Shaidah Jusoh
10.5120/1673-2257

Farhan Abdel-Fattah, Zulkhairi Md. Dahalin, Shaidah Jusoh . Article:Distributed and Cooperative Hierarchical Intrusion Detection on MANETs. International Journal of Computer Applications. 12, 5 ( December 2010), 32-40. DOI=10.5120/1673-2257

@article{ 10.5120/1673-2257,
author = { Farhan Abdel-Fattah, Zulkhairi Md. Dahalin, Shaidah Jusoh },
title = { Article:Distributed and Cooperative Hierarchical Intrusion Detection on MANETs },
journal = { International Journal of Computer Applications },
issue_date = { December 2010 },
volume = { 12 },
number = { 5 },
month = { December },
year = { 2010 },
issn = { 0975-8887 },
pages = { 32-40 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume12/number5/1673-2257/ },
doi = { 10.5120/1673-2257 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:00:55.499294+05:30
%A Farhan Abdel-Fattah
%A Zulkhairi Md. Dahalin
%A Shaidah Jusoh
%T Article:Distributed and Cooperative Hierarchical Intrusion Detection on MANETs
%J International Journal of Computer Applications
%@ 0975-8887
%V 12
%N 5
%P 32-40
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The wireless links between the nodes together with the dynamic-network nature of ad hoc network, increases the challenges of design and implement intrusion detection to detect the attacks. Traditional intrusion detection techniques have had trouble dealing with dynamic environments. In particular, issues such as collects real time attack related audit data and cooperative global detection. Therefore, we are motivated to design a new intrusion detection architecture which involves new detection technique to efficiently detect the abnormalities in the ad hoc networks. In this paper we present the architecture and operation of an intrusion detection technique in Mobile Ad hoc NETwork (MANET). The proposed model has distributed and cooperative architecture. The proposed intrusion detection technique combines the flexibility of anomaly detection with the accuracy of a signature-based detection method. In particular, we exploit machine learning techniques in order to achieve efficient and effective intrusion detection. A series of simulation and experimental results demonstrate that the proposed intrusion detection can effectively detect anomalies with low false positive rate, high detection rate and achieve higher detection accuracy.

References
  1. N.J. Puketza, K. Zhang, M. Chung, B. Mukherjee, and R.A. Olsson. A methodology for testing intrusion detection systems. Software Engineering, IEEE Transactions on, 22(10):719 –729, October 1996.
  2. Y. Xiao, X. Shen, Tiranuch Anantvalee, and Jie Wu. Chapter 7 a survey on intrusion detection in mobile ad hoc networks, 2006.
  3. Farhan Abdel-Fattah, Zulkhairi Md. Dahalin, and Shaidah Jusoh. Dynamic intrusion detection method for mobile ad hoc network using cpdod algorithm. IJCA Special Issue on MANETs, (1):22–29, 2010. Published by Foundation of Computer Science, USA.
  4. Li, Y and J Wei. Guidelines on Selecting Intrusion Detection Methods in MANET. In The Proceedings of the Information Systems Education Conference 2004, v 21 (Newport): §3233. ISSN: 1542-7382.
  5. Paul Brutch and Calvin Ko. Challenges in intrusion detection for wireless ad-hoc networks. In Proceedings of the 2003 Symposium on Applications and the Internet Workshops (SAINT’03 Workshops), SAINT-W’03, pages 368–, Washington, DC, USA, 2003. IEEE Computer Society.
  6. Yongguang Zhang and Wenke Lee. Intrusion detection in wireless adhoc networks. In Proceedings of the 6th annual international conference on Mobile computing and networking, MobiCom ’00, pages 275–283, New York, NY, USA, 2000. ACM.
  7. Patrick Albers, Olivier Camp, Jean marc Percher, Bernard Jouga, and Ricardo Puttini. Security in ad hoc networks: a general intrusion detection architecture enhancing trust based approaches. In In Proceedings of the First International Workshop on Wireless Information Systems (WIS-2002, pages 1–12, 2002.
  8. Yi-an Huang and Wenke Lee. A cooperative intrusion detection system for ad hoc networks. In Proceedings of the 1st ACM workshop on Security of ad hoc and sensor networks, SASN ’03, pages 135–147, New York, NY, USA, 2003. ACM.
  9. Oleg Kachirski and Ratan Guha. Intrusion detection using mobile agents in wireless ad hoc networks. In Proceedings of the IEEE Workshop on Knowledge Media Networking, pages 153–, Washington, DC, USA, 2002. IEEE Computer Society.
  10. Chin-Yang Tseng, Poornima Balasubramanyam, Calvin Ko, Rattapon Limprasittiporn, Jeff Rowe, and Karl Levitt. A specification-based intrusion detection system for aodv. In Proceedings of the 1st ACM workshop on Security of ad hoc and sensor networks, SASN ’03, pages 125–134, New York, NY, USA, 2003. ACM.
  11. Alex Gammerman and Volodya Vovk. Prediction algorithms and con_dence measures based on algorithmic randomness theory. Theor. Comput. Sci., 287(1):209_217, 2002.
  12. Glenn Shafer and Vladimir Vovk. A tutorial on conformal prediction. J. Mach. Learn. Res., 9:371–421, 2008.
  13. Yang Li, Binxing Fang, Li Guo, and You Chen. Network anomaly detection based on tcm-knn algorithm. In ASIACCS '07: Proceedings of the 2nd ACM symposium on Information, computer and communications security, pages 13_19, New York, NY, USA, 2007. ACM.
  14. Ke Zhang, Marcus Hutter, and Huidong Jin. A new local distancebased outlier detection approach for scattered real-world data. CoRR, abs/0903.3257, 2009.
  15. A. Mishra, K. Nadkarni, and A. Patcha. Intrusion detection in wireless ad hoc networks. Wireless Communications, IEEE, 11(1):48 – 60, February 2004.
  16. Yi-an Huang, Wei Fan, Wenke Lee, and Philip S. Yu. Cross-feature analysis for detecting ad-hoc routing anomalies. In ICDCS '03: Proceedings of the 23rd International Conference on Distributed Computing Systems, page 478, Washington, DC, USA, 2003. IEEE Computer Society.
  17. D. Sterne, P. Balasubramanyam, D. Carman, B. Wilson, R. Talpade, C. Ko, R. Balupari, C y. Tseng, T. Bowen, K. Levitt, and J. Rowe. A general cooperative intrusion detection architecture for manets. In In IWIA 05: Proceedings of the Third IEEE International Workshop on Information Assurance (IWIA05, pages 57–70. IEEE Computer Society, 2005.
  18. W J Ulivla. Evaluation of intrusion detection system. J. J. Res. Natl. Inst. Stand. Technol., 108(6):453–473, 2003.
  19. C.V. Zhou, S. Karunasekera, and C. Leckie. Evaluation of a decentralized architecture for large scale collaborative intrusion detection. In Integrated Network Management, 2007. IM ’07. 10th IFIP/IEEE International Symposium on, 21 2007.
  20. Bo Sun, Kui Wu, and Udo W. Pooch. Alert aggregation in mobile ad hoc networks. In Proceedings of the 2nd ACM workshop on Wireless security, WiSe ’03, pages 69–78, New York, NY, USA, 2003. ACM.
  21. Farhan A.F, Zulkhairi. D, and M.T. Hatim. Mobile agent intrusion detection system for mobile ad hoc networks: A non-overlapping zone approach. In Internet, 2008. ICI 2008. 4th IEEE/IFIP International Conference on, pages 1 –5, 2008.
  22. Erland Jonsson and Tomas Olovsson. A quantitative model of the security intrusion process based on attacker behavior. IEEE Trans. Softw. Eng., 23:235–245, April 1997.
  23. A. Karygiannis, E. Antonakakis, and A. Apostolopoulos. Host-based network monitoring tools for manets. In PE-WASUN ’06: Proceedings of the 3rd ACM international workshop on Performance evaluation of wireless ad hoc, sensor and ubiquitous networks, pages 153–157, New York, NY, USA, 2006. ACM.
  24. Hadi Otrok, Joey Paquet, Mourad Debbabi, and Prabir Bhattacharya. Testing intrusion detection systems in manet: A comprehensive study. Communication Networks and Services Research, Annual Conference on, 0:364–371, 2007.
  25. GloMoSim. Glomosim website, June 2007.
  26. Charles Perkins and Elizabeth Royer. Ad-hoc on-demand distance vector routing. In In Proceedings of the 2nd IEEE Workshop on Mobile Computing Systems and Applications, pages 90–100, 1997.
  27. C. Siva Ram Murthy and B.S. Manoj. Ad Hoc Wireless Networks: Architectures and Protocols. Prentice Hall PTR, Upper Saddle River, NJ, USA, 2004.
  28. Varun Chandola, Arindam Banerjee, and Vipin Kumar. Anomaly detection: A survey. ACM Comput. Surv., 41(3):1–58, 2009.
  29. Hongmei Deng, Roger Xu, Jason Li, Frank Zhang, Renato Levy, and Wenke Lee. Agent-based cooperative anomaly detection for wireless ad hoc networks. In ICPADS ’06: Proceedings of the 12th International Conference on Parallel and Distributed Systems, pages 613–620,
  30. Marcus A. Maloof. Machine Learning and Data Mining for Computer Security: Methods and Applications (Advanced Information and Knowledge Processing). Springer-Verlag New York, Inc., Secaucus, NJ, USA,2005.
Index Terms

Computer Science
Information Sciences

Keywords

MANET Intrusion detection CPDOD CP-KNN distributed and cooperative architecture intrusion detection Conformal Prediction