Intrusion Detection Using Fuzzy Stochastic Local Search Classifier

This paper proposes a stochastic local search classifier combined with the fuzzy logic concepts for intrusion detection. The proposed classifier works on knowledge base modeled as a fuzzy rule "if-then" and improved by using a stochastic local search. The method is tested on the Benchmark...

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Bibliographic Details
Main Authors: Bahamida, Bachir, Boughaci, D.
Format: Conference Proceeding
Language:English
Subjects:
Bayesian methods
classification
DARPA dataset
Expert systems
fuzzy logic
genetic algorithm
Genetic algorithms
Intrusion detection
Pragmatics
stochastic local search
Stochastic processes
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Summary:This paper proposes a stochastic local search classifier combined with the fuzzy logic concepts for intrusion detection. The proposed classifier works on knowledge base modeled as a fuzzy rule "if-then" and improved by using a stochastic local search. The method is tested on the Benchmark KDD'99 intrusion dataset and compared with other existing techniques for intrusion detection. The results are encouraging and demonstrate the benefit of the proposed approach.
DOI:10.1109/MICAI.2012.17