Journal Title : International Journal of Modern Trends in Engineering and Science

Author’s Name : M.Sindhu  unnamed

Volume 03 Issue 06 2016

ISSN no:  2348-3121

Page no: 56-63

Abstract – In multi -hop wireless ad hoc network link error and malicious packet dropping are two sources for packet losses. Whether  the losses are caused by link errors only, or by the combined effect of link errors and malicious drop are to be identified, can be known by observing a sequence of packet losses in the network. In this paper, while observing a sequence of packet losses in the network, we are interested in determining whether the losses are caused by link errors only, or by the combined effect of link errors and malicious drop. We are especially interested in the insider-attack case, whereby malicious nodes that are part of the route exploit their knowledge of the communication context to selectively drop a small amount of packets critical to the network performance. Because the packet dropping rate in this case is comparable to the channel error rate, conventional algorithms that are based on detecting the packet loss rate cannot achieve satisfactory detection accuracy. To improve the detection accuracy, we propose to exploit the correlations between lost packets. Furthermore, to ensure truthful calculation of these correlations, we develop a Homomorphic linear authenticator (HLA) based public auditing architecture that allows the detector to verify the truthfulness of the packet loss information reported by nodes. This construction is privacy preserving, collusion proof, and incurs low communication and storage overheads. To reduce the computation overhead of the baseline scheme, a packet-block-based mechanism is also proposed, which allows one to trade detection accuracy for lower computation complexity. The packet drop detection doesn’t send the complete data to the destination. The alternate route discovery and the destination should be authorized before the block of packets decode. Through extensive simulations, we verify that the proposed mechanisms achieve significantly better detection accuracy than conventional methods such as a maximum-  likelihood based detection.

KeywordsHomomorphic, HLA(Homomorphic Linear Authenticator), Denial-of-Service(DoS) 


  1. J. N. Arauz, “802.11 Markov channel modeling,” Ph.D. dissertation, School Inform. Sci., Univ. Pittsburgh, Pittsburgh, PA, USA, 2004.
  2. C. Ateniese, R. Burns, R. Curtmola, J. Herring, L. Kissner, Z.Peterson, and D. Song, “Provable data possession at untrusted stores,” in Proc. ACM Conf. Comput. and Commun. Secur., Oct. 2007, pp. 598–610.
  3. G. Ateniese, S. Kamara, and J. Katz, “Proofs of storage from homomorphic identification protocols,” in Proc. Int. Conf. Theory Appl.Cryptol. Inf. Security, 2009, pp. 319–333.
  4. B. Awerbuch, R. Curtmola, D. Holmer, C. Nita-Rotaru, and H. Rubens, “ODSBR: An on-demand secure byzantine resilient routing protocol for wireless ad hoc networks,”ACM Trans. Inform.Syst. Security, vol. 10, no. 4, pp. 1–35, 2008.
  5. B. Awerbuch, R. Curtmola, D. Holmer, C. Nita-Rotaru, and H. Rubens, “ODSBR: An on-demand secure byzantine resilient routing protocol for wireless ad hoc networks,” ACM Trans. Inf. Syst. Secur., vol. 10, no. 4, pp. 11–35, 2008.
  6. K. Balakrishnan, J. Deng, and P. K. Varshney, “TWOACK: Preventing selfishness in mobile ad hoc networks,” in Proc. IEEE Wireless Commun. Netw. Conf., 2005, pp. 2137–2142.
  7. D. Boneh, B. Lynn, and H. Shacham, “Short signatures from the weil pairing,” J. Cryptol., vol. 17, no. 4, pp. 297–319, Sep. 2004.
  8. S. Buchegger and J. Y. L. Boudec, “Performance analysis of the confidant protocol (cooperation of nodes: Fairness in dynamic adhoc networks),” in Proc. 3rd ACM Int. Symp. Mobile Ad Hoc Netw.Comput. Conf., 2002, pp. 226–236.
  9. L. Buttyan and J. P. Hubaux, “Stimulating cooperation in selforganizing mobile ad hoc networks,” ACM/Kluwer Mobile Netw.Appl., vol. 8, no. 5, pp. 579–592, Oct. 2003.
  10. J. Crowcroft, R. Gibbens, F. Kelly, and S. Ostring, “Modelling incentives for collaboration in mobile ad hoc networks,” presented at the First Workshop Modeling Optimization Mobile, AdHoc Wireless Netw., Sophia Antipolis, France, 2003.
  11. J. Eriksson, M. Faloutsos, and S. Krishnamurthy, “Routing amid colluding attackers,” in Proc. IEEE Int. Conf. Netw. Protocols, 2007, pp. 184–193.
  12. W. Galuba, P. Papadimitratos, M. Poturalski, K. Aberer, Z. Despotovic, and W. Kellerer, “Castor: Scalable secure routing for ad hoc networks,” in Proc. IEEE INFOCOM, Mar. 2010, pp. 1 –9.
  13. T. Hayajneh, P. Krishnamurthy, D. Tipper, and T. Kim, “Detecting malicious packet dropping in the presence of collisions and channel errors in wireless ad hoc networks,” in Proc. IEEE Int. Conf.Commun., 2009, pp. 1062–1067.
  14. Q. He, D. Wu, and P. Khosla, “Sori: A secure and objective reputation- based incentive scheme for ad hoc networks,” in Proc. IEEE Wireless Commun. Netw. Conf., 2004, pp. 825–830.
  15. D. B. Johnson, D. A. Maltz, and J. Broch, “DSR: The dynamic source routing protocol for multi-hop wireless ad hoc networks,” in Ad Hoc Networking. Reading, MA, USA: Addison-Wesley, 2001,ch. 5, pp. 139–172.
  16. W. Kozma Jr. and L. Lazos, “Dealing with liars: Misbehavior identification via Renyi-Ulam games,” presented at the Int.ICST Conf. Security Privacy in Commun. Networks, Athens, Greece, 2009.
  17. W. Kozma Jr., and L. Lazos, “REAct: Resource-efficient accountability for node misbehavior in ad hoc networks based on random audits,” in Proc. ACM Conf. Wireless Netw. Secur., 2009, pp. 103–110.
  18. K. Liu, J. Deng, P. Varshney, and K. Balakrishnan, “An acknowledgement-based approach for the detection of routing misbehavior in MANETs,” IEEE Trans. Mobile Comput., vol. 6, no. 5, pp. 536–550, May 2006.
  19. Y. Liu and Y. R. Yang, “Reputation propagation and agreement in mobile ad-hoc networks,” in Proc. IEEE WCNC Conf., 2003,pp. 1510–1515.
  20. S. Marti, T. J. Giuli, K. Lai, and M. Baker, “Mitigating routing misbehavior in mobile ad hoc networks,” in Proc. ACM MobiCom Conf., 2000, pp. 255–265.
  21. G. Noubir and G. Lin, “Low-power DoS attacks in data wireles lans and countermeasures,” ACM SIGMOBILE Mobile Comput.Commun. Rev., vol. 7, no. 3, pp. 29–30, Jul. 2003.
  22. V. N. Padmanabhan and D. R. Simon, “Secure traceroute to detect faulty or malicious routing,” in Proc. ACM SIGCOMM Conf., 2003, pp. 77–82.
  23. P. Papadimitratos and Z. Haas, “Secure message transmission in mobile ad hoc networks,” Ad Hoc Netw., vol. 1, no. 1, pp. 193–209,2003.
  24. A. Proano and L. Lazos, “Selective jamming attacks in wireless networks,” in Proc. IEEE ICC Conf., 2010, pp. 1–6.
  25. A. Proano and L. Lazos, “Packet-hiding methods for preventing selective jamming attacks,” IEEE Trans. Depend. Secure Comput., vol. 9, no. 1, pp. 101–114, Jan./Feb. 2012.