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An enhanced intrusion detection system for mobile ad-hoc network based on traffic analysis

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Abstract

The problem of intrusion detection in MANET’s has been approached in different dimension in this paper. This paper proposes a novel system network information based moderation model to identify and alleviate routing attacks. The proposed system uses time variant snapshots to detect routing attacks. Each node learns network details using the network information theory (NIT) to get the knowledge about the nodes of network, the neighbor locations, energy details, displacement speed from the route discovery packets and reply packets. From the learned details each node constructs the network topology at each time window to perform intrusion detection. At each packet reception, the node performs intrusion detection using NIT and TVS learned. The proposed technique has delivered effective outcome in mitigation of intrusion detection in mobile ad-hoc networks and improves the performance to a higher level.

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References

  1. Marchang, N., Datta, R., Das, S.K.: A novel approach for efficient usage of intrusion detection system in mobile ad-hoc networks. IEEE Trans. Veh. Technol. 66(2), 1684–1695 (2017)

    Article  Google Scholar 

  2. Kumar, S., Dutta, K.: Intrusion detection in mobile ad hoc networks: techniques, systems, and future challenges. J. Secur. Commun. Netw. 9(14), 2484–2556 (2016)

    Article  Google Scholar 

  3. Dorri, A., Kamel, S.R., Kheyrkhah, E.: Security challenges in mobile ad hoc networks: a survey. Int. J. Comput. Sci. Eng. Surv. 6(1), 1–7 (2015)

    Article  Google Scholar 

  4. Chourasia, .R, Boghey, R.K.: Novel IDS security against attacker routing misbehavior of packet dropping in MANET. In: Proceedings of the IEEE 7th International Conference on Cloud Computing, Data Science & Engineering—Confluence, pp. 456–460 (2017)

  5. Prasanna Lakshmi, G.S., Kumar, S., Patil, B.: Signature intrusion detection using a zone based AODV routing protocol for MANETs. In: Proceedings of the 4th International IEEE Conference on Advanced Computing and Communication Systems (ICACCS), pp. 1–7 (2017)

  6. Sankaranarayanan, S., Murugaboopathi, G.: Secure intrusion detection system in mobile ad hoc networks using RSA algorithm. In: Proceedings of the Second International Conference on Recent Trends and Challenges in Computational Models (ICRTCCM), pp. 354–357 (2017)

  7. Nanaware, P.M., Babar, S.D.: Trust system based intrusion detection in mobile ad hoc network (MANET). In: Proceedings of the IEEE International Conference on Next Generation Intelligent Systems (ICNGIS), pp. 1–4 (2016)

  8. Carvalho, J.M.A., Costa, P.C.G.: Collaborative approach for a MANET intrusion detection system using multilateration. In: Proceedings of the 11th IEEE International Conference on Computer Engineering & Systems (ICCES). pp. 59–65 (2016)

  9. Korba, A.A., Nafaa, M., Ghamri-Doudane, Y.: Anomaly-based intrusion detection system for ad-hoc networks. In: Proceedings of the 7th IEEE International Conference on the Network of the Future (NOF), pp. 1–3 (2016)

  10. Carvalho, J.M.A., Costa, P.C.G.: CMIDS: collaborative MANET intrusion detection system. In: Proceedings of the IEEE International Conference on Cyber Conflict (CyCon U.S.), pp. 1–5 (2016)

  11. Nemade, D., Bhole, A.T.: Performance evaluation of EAACK IDS using AODV and DSR routing protocols in MANET. In: Proceedings of the International Conference on Emerging Research in Electronics, Computer Science and Technology (ICERECT), pp. 126–131 (2015)

  12. Kazi, S.B., Adhoni, M.A.: Secure intrusion detection system to detect malevolent node in MANETs. In: Proceedings of the International Conference on Electrical, Electronics and Optimization Techniques (ICEEOT), pp. 1363–1368 (2016)

  13. Suresh, A., Reyana, A., Varatharajan, R.: CEMulti-core architecture for optimization of energy over heterogeneous environment with high performance smart sensor devices. Wirel. Pers. Commun. (2018). https://doi.org/10.1007/s11277-018-5504-0

    Article  Google Scholar 

  14. Suresh, A., Varatharajan, R.: Competent resource provisioning and distribution techniques for cloud computing environment. Cluster Comput. (2017). https://doi.org/10.1007/s10586-017-1293-6

    Article  Google Scholar 

  15. Chinnasamy, A., Sivakumar, B., Selvakumari, P., Suresh, A.: Minimum connected dominating set based RSU allocation for smartCloud vehicles in VANET. Clust. Comput. (2018). https://doi.org/10.1007/s10586-018-1760-8

    Article  Google Scholar 

  16. Sobh, T.S., Mostafa, W.M.: A cooperative immunological approach for detecting network anomaly. Appl. Soft Comput. J. 11(1), 1275–1283 (2011)

    Article  Google Scholar 

  17. Macia-Perez, F., Mora-Gimeno, F.J., Marcos-Jorquera, D., Gil-Martinez-Abarka, J.A.: Network intrusion detection system embedded on a smart sensor. IEEE Trans. Ind. Electron. 58(3), 722–732 (2011)

    Article  Google Scholar 

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Bala, K., Jothi, S. & Chandrasekar, A. An enhanced intrusion detection system for mobile ad-hoc network based on traffic analysis. Cluster Comput 22 (Suppl 6), 15205–15212 (2019). https://doi.org/10.1007/s10586-018-2545-9

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  • DOI: https://doi.org/10.1007/s10586-018-2545-9

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