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The authors present a robust intrusion detection approach for wireless networks based on a new multi-matrix visualization method with a set of pattern generation, evaluation, organization, and interaction functions. Their approach concentrates on assisting users to analyze statistical network topology patterns that could expose significant attack features. Specifically, they investigate Sybil attacks that have severe impacts on the fundamental operations of wireless networks. They have analyzed the features of network topologies under various Sybil attacks and, consequently, designed several matrix reordering algorithms to generate statistical patterns. These topology patterns are automatically evaluated and classified through the measured structural similarities to the signature attack patterns.
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