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Abstract: In this paper we describe a data mining framework for constructing intrusion detection models. The first key idea is to mine system audit data for consistent and useful patterns of program and user behavior. The other is to use the set of relevant system features presented in the patterns to compute inductively learned classifiers that can recognize anomalies and known intrusions. In order for the classifiers to be effective intrusion detection models, we need to have sufficient audit data for... (Update)
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BibTeX entry: (Update)
W. Lee, S. J. Stolfo, and K. W. Mok. Adaptive intrusion detection: a data mining approach. Artificial Intelligence Review, 1999. to appear. http://citeseer.ist.psu.edu/lee00adaptive.html More
@article{ lee00adaptive,
author = "Wenke Lee and Salvatore J. Stolfo and Kui W. Mok",
title = "Adaptive Intrusion Detection: A Data Mining Approach",
journal = "Artificial Intelligence Review",
volume = "14",
number = "6",
pages = "533--567",
year = "2000",
url = "citeseer.ist.psu.edu/lee00adaptive.html" }
Citations (may not include all citations):921 Mining Association Rules between Sets of Items in Large Data.. - Agrawal, Imielinski et al. - 1993
340 Mining Sequential Patterns - Agrawal, Srikant - 1995
248 Fast Effective Rule Induction - Cohen - 1995
213 Discovery of Multiple-Level Association Rules from Large Dat.. - Han, Fu - 1995
189 Discovering Frequent Episodes in Sequences (context) - Mannila, Toivonen et al. - 1995
142 A Sense of Self for Unix Processes - Forrest, Hofmeyr et al. - 1996
137 Finding Interesting Rules from Large Sets of Discovered Asso.. - Klemettinen, Mannila et al. - 1994
121 Mining Association Rules with Item Constraints - Srikant, Vu et al. - 1997
105 State Transition Analysis: A Rule-Based Intrusion Detection .. - Ilgun, Kemmerer et al. - 1995
86 JAM: Java Agents for Meta-Learning over Distributed Database.. - Stolfo, Prodromidis et al. - 1997
85 Discovering Generalized Episodes Using Minimal Occurrences - Mannila, Toivonen - 1996
84 Data Mining Approaches for Intrusion Detection - Lee, Stolfo - 1998
78 Security Problems in the TCP/IP Protocol Suite - Bellovin - 1989
59 Toward Parallel and Distributed Learning by Meta-Learning - Chan, Stolfo - 1993
58 available via anonymous ftp to ftp (context) - Jacobson, Leres et al. - 1989
57 Decision Tree Induction Based on Efficient Tree Restructurin.. - Utgoff, Berkman et al. - 1997
56 Clustering Association Rules - Lent, Swami et al. - 1997
49 Adaptive Fraud Detection - Fawcett, Provost - 1997
35 Mining Audit Data to Build Intrusion Detection Models - Lee, Stolfo et al. - 1998
32 A Software Architecture to Support Misuse Intrusion Detectio.. - Kumar, Spafford - 1995
30 The Architecture of a Network Level Intrusion Detection Syst.. (context) - Heady, Luger et al. - 1990
25 Sequence Matching and Learning in Anomaly Detection for Comp.. - Lane, Brodley - 1997
23 Detecting Intruders in Computer Systems - Lunt - 1993
19 Mining in a Data-flow Environment: Experience in Network Int.. - Lee, Stolfo et al. - 1999
9 A Real-time Intrusion Detection Expert System (IDES) - final.. (context) - Lunt, Tamaru et al. - 1992
4 Test Center Comparison: Network Intrusion-detection Solution.. (context) - McClure, Scambray et al. - 1998
4 Unix System Security (context) - Grampp, Morris - 1984
1 Fast Algorithms for Mining Association Rules (context) - Mining, Adaptive et al. - 1994
The graph only includes citing articles where the year of publication is known.
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