Intrusion detection based on clustering genetic algorithm

A novel approach of using clustering genetic algorithms is put forward to solve the computer network intrusion detection problem. This algorithm includes two steps which are clustering step and genetic optimizing step. The algorithm can not only cluster the cases automatically, but also detect the unknown intruded action. The results showed that this algorithm was successfully able to detect intruded action. The final model produced had an overall accuracy level of 95%, which showed both a high detection rate and an extremely low false alarm rate. From these results, it was concluded that clustering genetic algorithms are a viable method for computer intrusion detection.