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Author(s):
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Kanthakumar Pongaliur, Michigan State University, USA ; Li Xiao, Michigan State University, USA; Alex Liu, Michigan State University, USA
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Abstract:
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Compromised sensor nodes may collude to segregate a specific region of the sensor network preventing event reporting packets in this region from reaching the basestation. Additionally, they can cause skepticism over all data collected. Identifying and segregating such compromised nodes while identifying the type of attack with a certain confidence is critical to the smooth functioning of a sensor network. Existing work specializes in preventing or identifying specific type of attack and lacks a unified architecture to identify multiple attack types. Camouflage Event Based Malicious Node Detection Architecture (CENDA) is a proactive architecture that uses camouflage events generated by mobile-nodes to detect malicious nodes while identifying the type of attack. We exploit the spatial and temporal information of camouflage event while analyzing the packets to identify malicious activity. We simulated CENDA to compare its performance with other techniques that provide protection against individual attack types and the results show marked improvement in malicious node detection while having significantly less false positives. Moreover, CENDA is able to identify the type of malicious activity and is flexible to be configured to include other attack types in future.
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