Guy Helmer, Johnny Wong, Vasant Honavar, Les Miller  Home/Search
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Abstract: We examine the effectiveness of rule learning to detect intrusions against privileged programs, using a feature vector representation to describe the system calls executed by each process. We then use the genetic algorithm approach to feature subset selection to show that we can reduce the number of features observed while maintaining or improving learning accuracy. Therefore, the amount of data that must be obtained from running processes is reduced. This application of artificial intelligence ... (Update)
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BibTeX entry: (Update)
Helmer Guy, Wong Johnny S, H. V. (1999). Automated discovery of concise predictive rules for intrusion detection. In Proceedings of AAAI'99. http://citeseer.ist.psu.edu/article/helmer99automated.html More
@techreport{ helmer.tr.99,
author = "Guy Helmer and Johnny Wong and Vasant Honavar and Les Miller",
title = "Automated Discovery of Concise Predictive Rules for Intrusion
Detection",
type = "Technical Report",
number = "99-01",
institution = "Department of Computer, Iowa State University",
year = 1999,
month = "January",
url = "citeseer.ist.psu.edu/article/helmer99automated.html" }
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