Evolutionary Algorithm and Its Application in Artificial Immune System

Analyses were made on the basic principles of evolutionary algorithm, evolution strategies and evolution programming. Considering the superiority of evolutionary algorithm in intellectual computing, we analyze a typical optimizing algorithm for artificial immune system (AIS). Combining evolutionary algorithm and artificial immunity, we present an immune intrusion analysis scheme based on statistical analyzing model. The scheme introduces the prominent characteristics of evolutionary algorithm, such as parallel operating, successive optimizing into intrusion parameter selecting, data collecting and intrusion analyzing, thus it effectively improves the applicableness of immune IDS. The scheme avoids the security threats and weakness arising from the transfer of immune pathology metaphor mechanisms into AIS. As a comparison with other artificial immune schemes, we also provide an application case of the immune analyzing scheme in intrusion detecting and dealing, the comparison further justifies the scheme´s adaptability, stability, robustness and parallel operating regarding its application in software and hardware circumstances.