Intrusion Detection Using Data Mining Along Fuzzy Logic and Genetic Algorithms

Intrusion Detection is one of the important area of research. Our work has explored the possibility of integrating the fuzzy logic with Data Mining methods using Genetic Algorithms for intrusion detection. The reasons for introducing fuzzy logic is two fold, the first being the involvement of many quantitative features where there is no separation between normal operations and anomalies. Thus fuzzy association rules can be mined to find the abstract correlation among different security features. We have proposed architecture for Intrusion Detection methods by using Data Mining algorithms to mine fuzzy association rules by extracting the best possible rules using Genetic Algorithms.