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A Novel Computational Modelling to Optimize the Utilization of Intrusion Detection Paradigm in a Large-Scale MANET

  • Najiya Sultana
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 765)

Abstract

Over the past decade, mobile ad-hoc networks (MANET) gained the attention of researchers and became a key technology in many aspects owing to its potential applicability and increased usage in providing efficient wireless networking. The ability of enabling an instant temporary wireless networking scenario in situations like flooding and defense made MANET a prominent domain of research. Although, it has been extensively studied with respect to different means of issues including network security, power consumption issues etc. but the core findings in the area of security were found mostly limited to theoretical contributions. Moreover, An intrusion detection systems (IDS) enable different procedures involved into monitoring the activities being exercised in a MANET whether; it poses any suspicious or malicious events that could be harmful for the entire system. The conventional IDS models are more likely to consume higher level of energy which minimizes the network lifetime owing to rapid depletion of node’s battery power. The study thereby primarily addressed this issue and come up with an efficient scheme which targets to optimize the time period in which IDS remain busy in a large-scale MANET. It also incorporated a technique which relates probabilistic theory of optimization to bring an effective cooperation among IDSs and neighbor nodes which leads to reduce their individual busy time. The proposed approach aims to reduce busy time of individual IDS while maintaining their effectiveness towards achieving defined tasks. To support the performance efficiency the proposed study developed an algorithm and simulated it over a numerical computing tool in terms of different performance parameters.

Keywords

Mobile ad-hoc networks Intrusion detection systems Energy consumption optimization 

References

  1. 1.
    Zeadally, S., Hunt, R., Chen, Y.-S., Irwin, A., Hassan, A.: Vehicular ad hoc networks (VANETS): status, results, and challenges. Telecommun. Syst. 50(4), 217–241 (2012)CrossRefGoogle Scholar
  2. 2.
    Bhoi, S.K., Khilar, P.M.: Vehicular communication: a survey. IET Netw. 3(3), 204–217 (2014)CrossRefGoogle Scholar
  3. 3.
    Marti, S., Giuli, T.J., La, K., Baker, M.: Mitigating routing misbehavior in a mobile ad-hoc environment. In: Proceedings of the 6th Annual ACM/IEEE International Conference on Mobile Computing and Networking, pp. 255–265, August 2000Google Scholar
  4. 4.
    Bernsen, J., Manivannan, D.: Unicast routing protocols for vehicular ad hoc networks: a critical comparison and classification. Pervasive Mob. Comput. 5(1), 1–18 (2009)CrossRefGoogle Scholar
  5. 5.
    Kumar, R., Dave, M.: A comparative study of various routing protocols in VANET, CoRR, vol. abs/1108.2094 (2011)Google Scholar
  6. 6.
    Zhang, M., Wolff, R.S.: A border node based routing protocol for partially connected vehicular ad hoc networks. J. Commun. 5(2), 130–143 (2010)CrossRefGoogle Scholar
  7. 7.
    Hoang Hai, T., Huh, E.-N.: Optimal selection and activation of intrusion detection agents for wireless sensor networks. In: Proceedings of the Future Generation Communication and Networking (FGCN 2007), vol. 1, pp. 350–355, 6–8 December 2007Google Scholar
  8. 8.
    Fitaci, S.M., Jaffres-Runser, K., Comaniciu, C.: On modeling energy-security trade-offs for distributed monitoring in wireless ad hoc networks. In: Proceedings of the Military Communications Conference, MILCOM 2008, pp. 1–7. IEEE, 16–19 November 2008Google Scholar
  9. 9.
    Clegg, R.G., Clayman, S., Pavlou, G., Mamatas, L., Galis, A.: On the selection of management/monitoring nodes in highly dynamic networks. IEEE Trans. Comput. 62(6), 1207–1220 (2013)MathSciNetCrossRefzbMATHGoogle Scholar
  10. 10.
    Dong, D., Liao, X., Liu, Y., Shen, C., Wang, X.: Edge self-monitoring for wireless sensor networks. IEEE Trans. Parallel Distrib. Syst. 22(3), 514–527 (2011)CrossRefGoogle Scholar
  11. 11.
    Khalil, I., Bagchi, S., Shroff, N.B.: SLAM: sleep-wake aware local monitoring in sensor networks. In: Proceedings of the 37th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2007), pp. 565–574 (2007)Google Scholar
  12. 12.
    Zheng, R., Le, T., Han, Z.: Approximate online learning algorithms for optimal monitoring in multi-channel wireless networks. IEEE Trans. Wirel. Commun. 13(2), 1023–1033 (2014)CrossRefGoogle Scholar
  13. 13.
    Tsikoudis, N., Papadogiannakis, A., Markatos, E.P.: LEoNIDS: a low-latency and energy-efficient network-level intrusion detection system. IEEE Trans. Emerg. Top. Comput. PP(99) (2014)Google Scholar
  14. 14.
    Muradore, R., Quaglia, D.: Energy-efficient intrusion detection and mitigation for networked control systems security. IEEE Trans. Ind. Inform. 11(3), 830–840 (2015)CrossRefGoogle Scholar
  15. 15.
    Shen, S.: A game-theoretic approach for optimizing intrusion detection strategy in WSNs. In: Proceedings of the 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce (AIMSEC), pp. 4510–4513, 8–10 August 2011Google Scholar
  16. 16.
    Afgah, A., Das, S.K., Basu, K.: A non-cooperative game approach for intrusion detection in sensor networks. In: Proceedings of the VTC 2004, Fall 2004Google Scholar
  17. 17.
    Alpcan, T., Basar, T.: A game theoretic approach to decision and analysis in network intrusion detection. In: Proceedings of the 43rd IEEE Conference on Decision and Control, December 2004Google Scholar
  18. 18.
    Liu, Y., Man, H., Comaniciu, C.: A game theoretic approach to efficient mixed strategies for intrusion detection. In: Proceedings of the IEEE International Conference on Communications (ICC 2006) (2006)Google Scholar

Copyright information

© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringTAIBAH UniversityMedinaSaudi Arabia

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