Abstract
It is required to realize practically useful masquerade detection for secure environments. In this paper, we propose a new masquerade detection method, which is based on support vector machine and using co-occurrence matrix. Our method can be performed with low cost and achieve good detection rate. We also consider online update for adapting to changes of modeled users’ behaviors. We report some experimental results showing our method would be able to work well in real situations.
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Chen, L., Aritsugi, M. (2006). An SVM-Based Masquerade Detection Method with Online Update Using Co-occurrence Matrix. In: Büschkes, R., Laskov, P. (eds) Detection of Intrusions and Malware & Vulnerability Assessment. DIMVA 2006. Lecture Notes in Computer Science, vol 4064. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11790754_3
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DOI: https://doi.org/10.1007/11790754_3
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36014-8
Online ISBN: 978-3-540-36017-9
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