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Adaptive CUSUM Algorithm to Detect Malicious Behaviors in Wireless Mesh Networks

Abstract : Wireless mesh networks (WMNs) are very attractive networks as they are low cost and able to extend Internet rapidly in areas where other networks (e.g., Wi-Fi, MANETs, wired networks, 3G) cannot access due to their technical and/or economical limitations. However, these networks have to deal with security issues which prevent their deployment. In this paper, we propose a new reputation scheme which aims at preventing nodes from falsely detecting their neighbors as misbehaving due to packet loss over their links. The proposed reputation scheme is based on the fact that a link’s packet loss ratio, when it is computed over a large quantity of observations, is quite stable over time. To detect misbehaving neighbors, a node, via its IDS, compares with the statistical method CUSUM (cumulative sum control chart) whether the distribution of packet loss rate observed for each of its neighbors follows the expected distribution or not. The validation of our solution shows that it allows to assign to nodes a trust value which reflects their real behavior.
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Juliette Dromard, Rida Khatoun, Lyes Khoukhi. Adaptive CUSUM Algorithm to Detect Malicious Behaviors in Wireless Mesh Networks. 8th IFIP International Conference on Autonomous Infrastructure, Management and Security (AIMS), Jun 2014, Brno, Czech Republic. pp.29-41, ⟨10.1007/978-3-662-43862-6_3⟩. ⟨hal-01401284⟩

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