Intrusion Detection System Using Fuzzy Genetic Algorithm With Feature Selection
Intrusion detection now a day is increasingly important aspect of computer security. Various approaches have been applied in past that are less effective to curb the menace of intrusion. The purpose of this paper is to provide an Intrusion Detection System (IDS), by applying fuzzy-genetic algorithm with feature selection to network intrusion detection system. The authors have selected 10 most effective features on the basis of Information gain. Optimal subset of feature selection reduces the training time of the intrusion detection system. They fuzzify these reduced subset of features and gives as a input to genetic algorithm for rule generation. Generated rule can detect attack with more efficiency.