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The Intrusion Detection Systems (IDS) are becoming indispensable for effective protection against attacks that are constantly changing in magnitude and complexity. This paper proposes a Fuzzy Genetic Algorithm (FGA) for intrusion detection. The FGA system is a fuzzy classifier, whose knowledge base is modeled as a fuzzy rule such as "If-then" and improved by a genetic algorithm. The method is tested on the benchmark KDD'99 intrusion dataset and compared with other existing techniques available in this paper. The results are encouraging and demonstrate the benefits of the proposed approach.
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