Sleuthing Wormhole Attacks Using Hidden Markov Model in Wireless Networks

Sunitha M¹, Priyadharshini P²

^1,2GRT Institute of Engineering and Technology, Tiruttani

Abstract

Wireless networks are vulnerable to many attacks such as attacks like eavesdropping, man-in-the-middle, etc. Therefore, security assailability should be identified and safeguard against wireless networks.We bring out the wormhole attack, a severe attack in wireless networks that is particularly challenging to protect against. The wormhole attack is very powerful, and preventing the attack has proven to be very difficult. In the wormhole attack, an attacker captures packet at one location in the network, tunnels them to another location, and retransmits them there into the network. To struggle against wormhole attacks, we propose an anomaly-based detection system by using strategically distributed monitoring stubs (MSs).The MSs, by sniffing the traffic, extract features for detecting these attacks and construct normal usage behavior profiles. We have used a model called, Hidden Markov Model (HMM), to compute behavioral distance in order to compare the normal usage behavioral profiles to detect intrusions. The monitoring stubs produces sound alarm on the sender side when data gets attacked.

Keywords

• Wormhole attack, Mobile Ad hoc Network, Security, Intrusion detection

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Cite this Article as Follows

Sunitha M, Priyadharshini P. Sleuthing Wormhole Attacks Using Hidden Markov Model in Wireless Networks. International Conference on Innovative trends in Electronics Communication and Applications 2014. Vol. 1. Chennai: Association of Scientists, Developers and Faculties, 2014. 275-280. Print.