Integrated artificial immune system for intrusion detection - Yue-bing CHEN; Chao FENG; Quan ZHANG; Chao-jing TANG (Tongxin xuebao)
According to the practical requirements of intrusion detection,an integrated artificial immune system (IAIS) was proposed.The system combined dendritic cell algorithm(DCA)and negative selection algorithm(NSA).DCA was used to detect behavioral features.NSA was used to detect structural features.IAIS was validated on KDD 99 dataset.Comparisons to other approaches were made.The experimental results show that the detection performance of IAIS is comparable to classic classification algorithm.IAIS does not rely on labeled data to train detectors.It combines behavioral features and structural features to detect intrusions in real-time mode.