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One of the most challenging security concerns for network administrators is the presence of rogue access points. In this paper, the authors propose a statistical based approach to detect rogue access points using a Hidden Markov Model applied to passively measured packet-header data collected at a gateway router. Their approach utilizes variations in packet inter-arrival time to differentiate between authorized access points and rouge access points. They designed and developed their Hidden Markov Model by analyzing Denial of Service attacks and the traffic characteristics of 802.11 based Wireless Local Area Networks. Experimental validations demonstrate the effectiveness of their approach.
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