| Document Date: 2011-09-04 10:44:35
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City Newport Beach / Lake Taho / Portland / Berkman / / Company Computer Science Laboratory / AAAI Press / SRI International / / / Event Person Communication and Meetings / / Facility New York University / Kui W. Mok Computer Science Department Columbia University / / IndustryTerm data mining techniques / basic algorithms / data mining framework / smtp / system builders / intrusion detection systems / approximate mining procedure / end product / data mining / data mining algorithms / individual services / basic algorithm / level-wise approximate mining procedure / on-line algorithms / misuse detection systems / intrusionspecific tools / anomaly detection systems / frequent episodes algorithm / frequent episodes algorithms / graphical tool / iterative level-wise approximate mining procedure / data pre-processing / mining / frequency services / login / learning algorithms / / Movie A. I. / / Organization Clustering association / Columbia University / New York University / National Science Foundation / X. An association / Mining association / / Person Wenke Lee / Charles Elkan / Morgan Kaufmann / Alexander Tuzhilin / Salvatore J. Stolfo / / Position Governor / representative / / ProvinceOrState North Carolina / California / / PublishedMedium Machine Learning / IEEE Transactions on Software Engineering / / Technology basic algorithms / expert system / on-line algorithms / on-line learning algorithms / machine learning / Axis Attribute(s) These basic algorithms / tcp/ip protocol / TCP/IP / frequent episodes algorithm / Knowledge Management / artificial intelligence / Java / data mining algorithms / frequent episodes algorithms / two basic algorithms / http / data mining / basic algorithm / / URL www.aaai.org / http /
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Mining Audit Data to Build Intrusion Detection Models∗ Wenke Lee and Salvatore J. Stolfo and Kui W. Mok Computer Science Department Columbia University 500 West 120th Street, New York, NY 10027 {wenke,sal,mok}@cs.colum