Application of Particle Swarm Optimization to Clustering for Intrusion Detection
Hongying Zheng, Meiju Hou, Yu Wang · International Symposium on Parallel Architectures, Algorithms and Programming · 2010
Keeping networks security has never been such an imperative task as today. In this paper, by combining particle swarm optimization and clustering algorithm, a new detection method, Intrusion Detection based on Unsupervised Clustering and PSO algorithm (IDCPSO), is proposed. Particle swarm optimization algorithm is used to optimize the clustering results and obtain the optimal detection result. IDCPSO needs unlabeled data for training and automatically establish clusters and detect intruders by labeling normal and abnormal groups. Computer experiment results with KDD cup show that this algorithm is effective for intrusion detection.