The role of KL divergence in anomaly detection

Publication Type:
Conference Proceeding
Citation:
Performance Evaluation Review, 2011, 39 (1 SPEC. ISSUE), pp. 123 - 124
Issue Date:
2011-07-15
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We study the role of Kullback-Leibler divergence in the framework of anomaly detection, where its abilities as a statistic underlying detection have never been investigated in depth. We give an in-principle analysis of network attack detection, showing explicitly attacks may be masked at minimal cost through 'camouflage'. We illustrate on both synthetic distributions and ones taken from real traffic.
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