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FJADA: Friendship Based JellyFish Attack Detection Algorithm for Mobile Ad Hoc Networks

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Abstract

TCP and UDP are considered the most popular and well known transport layer protocols to facilitate the end to end communication between two nodes in the network. TCP is used as the transport layer protocol in packet delivery and error sensitive applications, where packet loss cannot be compromised. However, low-rate TCP targeted Denial of Service (DoS) attacks exploit the retransmission timeout and congestion control features of TCP protocol. These low-rate TCP targeted Denial of Service (DoS) attacks are also called JellyFish (JF) attacks. These attacks perform the malicious activities either by delaying, or periodically dropping or mis-ordering the data packets on the route from source to destination node in the network, and cause severe degradation in end-to-end throughput in the network. JellyFish attack is further classified as JF-Delay Variance Attack, JF-Periodic Drop Attack and JF-Reorder Attack based on the type of the malicious activities being performed. JellyFish attack conforms to all existing routing and packet forwarding protocol specifications, and therefore it becomes very difficult to detect its presence in the network. In this paper, a Friendship Based JellyFish Attack Detection Algorithm (FJADA) is presented for Mobile Ad Hoc Networks, where the basic concept of friendship mechanism is added to the existing Direct Trust-based Detection (DTD) algorithm to save the valuable resources of a node in monitoring the activities of its one hop neighbours, through promiscuous mode. FJADA also minimizes the possibility of overestimating the malicious behaviour of innocent nodes due to radio transmission errors, network congestion or packet collisions. The results obtained throughout the simulation experiments clearly show the feasibility and effectiveness of the proposed detection algorithm.

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References

  1. Chlamtac, I., Conti, M., & Liu, J. J. N. (2003). Mobile ad hoc networking: imperatives and challenges. Ad Hoc Networks, 1(1), 13–64.

    Article  Google Scholar 

  2. Hoebeke, J., Moerman, I., Dhoedt, B., & Demeester, P. (2004). An overview of mobile ad hoc networks: Applications and challenges. Journal - Communications Network, 3(3), 60–66.

    Google Scholar 

  3. Kumar, S., & Dutta, K. (2016). Securing mobile ad hoc networks: Challenges and solutions. International Journal of Handheld Computing Research (IJHCR), 7(1), 26–76.

    Article  Google Scholar 

  4. Petrovic, M., & Aboelaze, M. (2003, February). Performance of TCP/UDP under ad hoc IEEE 802.11. In Proceedings of 10th IEEE international conference on telecommunications (ICT 2003) (Vol. 1, pp. 700–708). IEEE.

  5. Aad, I., Hubaux, J. P., & Knightly, E. W. (2004, September). Denial of service resilience in ad hoc networks. In Proceedings of the 10th annual international conference on mobile computing and networkingMobiCom ‘04 (pp. 202–215). ACM.

  6. Kuzmanovic, A., & Knightly, E. W. (2006). Low-rate TCP-targeted denial of service attacks and counter strategies. IEEE/ACM Transactions on Networking (TON), 14(4), 683–696.

    Article  Google Scholar 

  7. Aad, I., Hubaux, J. P., & Knightly, E. W. (2008). Impact of denial of service attacks on ad hoc networks. IEEE/ACM Transactions on Networking, 16(4), 791–802.

    Article  Google Scholar 

  8. Kumar, S., & Dutta, K. (2015). Intrusion detection technique for black hole attack in mobile ad hoc networks. International Journal of Information Privacy, Security and Integrity, 2(2), 81–101. https://doi.org/10.1504/IJIPSI.2015.075435.

    Google Scholar 

  9. Zapata, M. G. (2002). Secure ad hoc on-demand distance vector routing. ACM SIGMOBILE Mobile Computing and Communications Review, 6(3), 106–107.

    Article  Google Scholar 

  10. Razak, S. A., Furnell, S., Clarke, N., & Brooke, P. (2007). Building a trusted community for mobile ad hoc networks using friend recommendation. In E. Kranakis & J. Opatrny (Eds.), Ad-hoc, mobile, and wireless networks. ADHOC-NOW 2007. Lecture Notes in Computer Science (Vol. 4686, pp. 129–141). Berlin: Springer.

    Google Scholar 

  11. Laxmi, V., Lal, C., Gaur, M. S., & Mehta, D. (2015). JellyFish attack: Analysis, detection and countermeasure in TCP-based MANET. Journal of Information Security and Applications, 22, 99–112.

    Article  Google Scholar 

  12. Rodriguez-Mayol, A., & Gozalvez, J. (2014). Reputation based selfishness prevention techniques for mobile ad-hoc networks. Telecommunication Systems, 57(2), 181–195.

    Article  Google Scholar 

  13. Perkins, C. E. & Royer, E. M. (1999, February) Ad hoc on-demand distance vector routing. In Proceedings of second IEEE workshop on mobile computing systems and applications (WMCSA’99) (pp. 90–100). IEEE.

  14. Laxmi, V., Mehta, D., Gaur, M. S., & Faruki, P. (2013, November). Impact analysis of jellyfish attack on tcp-based mobile ad-hoc networks. In Proceedings of the 6th international conference on security of information and networks (pp. 189–195). ACM.

  15. Samad, F. (2011). Securing wireless mesh networks: a three dimensional perspective. Doctoral dissertation. RWTH Aachen University, Germany.

  16. Jayasingh, B. B., & Swathi, B. (2010). A novel metric for detection of JellyFish Reorder Attack on ad hoc network. BVICAM’s International Journal of Information Technology, 2(1), 164–169.

    Google Scholar 

  17. Samad, F., Abu Ahmed, Q., Shaikh, A., & Aziz, A. (2012). JAM: Mitigating jellyfish attacks in wireless ad hoc networks. In B. S. Chowdhry, F. K. Shaikh, D. M. A. Hussain, & M. A. Uqaili (Eds.), Emerging trends and applications in information communication technologies. IMTIC 2012. Communications in computer and information science (Vol. 281, pp. 432–444). Berlin: Springer.

    Google Scholar 

  18. Wazid, M., Katal, A., & Goudar, R. H. (2012, December). Cluster and super cluster based intrusion detection and prevention techniques for JellyFish Reorder Attack. In Proceedings of 2nd IEEE international conference on parallel, distributed and grid computing (PDGC-2012) (pp. 435–440). IEEE.

  19. Katal, A., Wazid, M., Goudar, R. H., & Singh, D. P. (2013, April). A cluster based detection and prevention mechanism against novel datagram chunk dropping attack in MANET multimedia transmission. In Proceedings of 2013 IEEE conference on information and communication technologies (ICT) (pp. 479–484). IEEE.

  20. Wazid, M., Katal, A., Sachan, R. S., & Goudar, R. H. (2013, April). E-TCP for efficient performance of MANET under JF delay variance attack. In Proceedings of 2013 IEEE conference on information and communication technologies (ICT) (pp. 145–150). IEEE.

  21. Patel, H. P., & Chaudhari, M. B. (2013, July). A time space cryptography hashing solution for prevention JellyFish Reordering Attack in wireless ad hoc networks. In Proceedings of 2013 fourth IEEE international conference on computing, communications and networking technologies (ICCCNT) (pp. 1–6). IEEE.

  22. Kumar, S., & Dutta, K. (2016). Intrusion detection in mobile ad hoc networks: Techniques, systems, and future challenges. Security and Communication Networks, 9(14), 2484–2556.

    Article  Google Scholar 

  23. Thomas, A., Sharma, V. K., & Singhal, G. (2015, December). Secure link establishment method to prevent jelly fish attack in MANET. In Proceedings of international conference on computational intelligence and communication networks (CICN) (pp. 1153–1158). IEEE.

  24. Razak, S. A., Furnell, S. M., Clarke, N. L., & Brooke, P. J. (2008). Friend-assisted intrusion detection and response mechanisms for mobile ad hoc networks. Ad Hoc Networks, 6(7), 1151–1167.

    Article  Google Scholar 

  25. Murata, T. (1989). Petri nets: Properties, analysis and applications. Proceedings of the IEEE, 77(4), 541–580.

    Article  Google Scholar 

  26. Wang, B., Chen, X., & Chang, W. (2014). A light-weight trust-based QoS routing algorithm for ad hoc networks. Pervasive and Mobile Computing, 13, 164–180.

    Article  Google Scholar 

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Correspondence to Sunil Kumar.

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Kumar, S., Dutta, K. & Garg, A. FJADA: Friendship Based JellyFish Attack Detection Algorithm for Mobile Ad Hoc Networks. Wireless Pers Commun 101, 1901–1927 (2018). https://doi.org/10.1007/s11277-018-5797-z

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