Research of intrusion detection based on genetic clustering algorithm

The presented intrusion detection algorithm based on clustering need to know the cluster number before it works in clustering process. Therefore, a new detection algorithm, the Network Anomaly Intrusion Detection based on Genetic Clustering (NAIDGC) algorithm is proposed in this paper. The cluster centers are binary encoded. The sum of the Euclidean distances of the points from their respective cluster centers is adopted as the similarity metric. The optimal cluster centers are chosen by the genetic algorithm. Hence, self-identification of invasions is achieved. The experimental results demonstrate that this method can detect intrusion data efficiently in the network environment.