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Detecting Wormhole Attacks in Wireless Networks Using Connectivity Information

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3 Author(s)
Maheshwari, R. ; Stony Brook Univ., Stony Brook ; Jie Gao ; Das, S.R.

We propose a novel algorithm for detecting worm-hole attacks in wireless multi-hop networks. The algorithm uses only connectivity information to look for forbidden substructures in the connectivity graph. The proposed approach is completely localized and, unlike many techniques proposed in literature, does not use any special hardware artifact or location information, making the technique universally applicable. The algorithm is independent of wireless communication models. However, knowledge of the model and node distribution helps estimate a parameter used in the algorithm. We present simulation results for three different communication models and two different node distributions, and show that the algorithm is able to detect wormhole attacks with a 100% detection and 0% false alarm probabilities whenever the network is connected with high probability. Even for very low density networks where chances of disconnection is very high, the detection probability remains very high.

Published in:

INFOCOM 2007. 26th IEEE International Conference on Computer Communications. IEEE

Date of Conference:

6-12 May 2007