NDLI: Improving Network Intrusion Detection by Means of Domain-Aware Genetic Programming

Content Provider	IEEE Xplore Digital Library
Author	Blasco, J. Orfila, A. Ribagorda, A.
Copyright Year	2010
Abstract	One of the central areas in network intrusion detection is how to build effective systems that are able to distinguish normal from intrusive traffic. In this paper we explore the use of Genetic Programming (GP) for such a purpose. Although GP has already been studied for this task, the inner features of network intrusion detection have been systematically ignored. To avoid the blind use of GP shown in previous research, we guide the search by means of a fitness function based on recent advances on IDS evaluation. For the experimental work we use a well-known dataset (i.e. KDD-99) that has become a standard to compare research although its drawbacks. Results clearly show that an intelligent use of GP achieves systems that are comparable (and even better in realistic conditions) to top state-of-the-art proposals in terms of effectiveness, improving them in efficiency and simplicity.
Starting Page	327
Ending Page	332
File Size	645876
Page Count	6
File Format	PDF
ISBN	9781424458790
e-ISBN	9781424458806
DOI	10.1109/ARES.2010.53
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2010-02-15
Publisher Place	Poland
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Availability effectiveness genetic programming efficiency Computerized monitoring Telecommunication traffic intrusion detection Proposals Computer science Computer network reliability Intrusion detection Genetic programming Computer networks Computer security
Content Type	Text
Resource Type	Article

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