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Some other applied techniques on intrusion detection problem are genetic algorithms

The purpose of this paper is to describe two objective fuzzy genetics-based learning algorithms and discusses its usage to detect intrusion in a computer network. Experiments were performed with KDD-cup data set, which have information on computer networks, during normal behavior and intrusive behavior. The performance of final fuzzy classification system has been investigated using intrusion detection problem as a high dimensional classification problem. This task is formulated as optimization problem with two objectives: To minimize the number of fuzzy rules and to maximize the classification rate. We show a two-objective genetic algorithm for finding non-dominated solutions of the fuzzy rule selection problem.