NDLI: Efficient Rule Generation for Cost-Sensitive Misuse Detection Using Genetic Algorithms

Content Provider	IEEE Xplore Digital Library
Author	Ashfaq, S. Farooq, M.U. Karim, A.
Copyright Year	2006
Description	Author affiliation: Lahore Univ. of Manage. Sci. (Ashfaq, S.; Farooq, M.U.; Karim, A.)
Abstract	This paper presents a genetic algorithm (GA) for generating efficient rules for cost-sensitive misuse detection in intrusion detection systems. The GA employs only the five most relevant features for each attack category for rule generation. Furthermore, it incorporates the different costs of misclassifying attacks in its fitness function to yield rules that are cost sensitive. The generated rules signal an attack as well as its category. The GA is implemented and evaluated on the KDDCup 99 dataset. Its detection performance is comparable to the winners of the KDDCup 99 competition. However, the rules generated by our GA are short and amenable for real time misuse detection
Starting Page	282
Ending Page	285
File Size	4592787
Page Count	4
File Format	PDF
ISBN	1424406048
DOI	10.1109/ICCIAS.2006.294138
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-11-03
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Costs Databases Intrusion detection Genetic programming Signal generators Computer network management Computer security Computational intelligence Pattern matching Genetic algorithms
Content Type	Text
Resource Type	Article

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Efficient Rule Generation for Cost-Sensitive Misuse Detection Using Genetic Algorithms