Detector optimization algorithm with co-evolution in immunity-based intrusion detection system

In the immunity-based intrusion detection system, the detector is the most important component. But, it has some problems should be solved before detection, and the detector optimization of security holes is a research hotspot. In this paper, analyzing the relationship with number of detector and detection performances, inspired by the species´ co-evolution in nature, a detector optimization algorithm with co-evolution is proposed. The experimental tests demonstrate that the algorithm can not only decrease the security holes but also achieve a more precise coverage of the nonself space with fewer detectors.