Immune Recognition Method Based on Analogy Reasoning in Intrusion Detection System

作     者：ZHANG Changyou CAO Yuanda YANG Minghua YU Jiong ZHU Dongfeng 

作者机构：School of Computer Science and Technology Beijing Institute of Technology Beijing 100081 China Computer Science and Technology Department Shijiazhuang Railway Institute Shijiazhuang 050043 Hebei China College of Information University Wulumuqi 830046 Science and Engineering Xinjiang Xinjiang China 

出 版 物：《Wuhan University Journal of Natural Sciences》 (武汉大学学报（自然科学英文版）)

年 卷 期：2006年第11卷第6期

页      面：1839-1843页

学科分类：08[工学] 081201[工学-计算机系统结构] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：Supported by the National Natural Science Foundation ofChina (60563002) Scientific Research Programof the Higher EducationInstitution of Xinjiang (XJEDU2004I03) 

主　　题：immune recognition analogy reasoning similarity genetic algorithm intrusion detection system 

摘      要：In this paper, we propose an analogy based immune recognition method that focuses on the implement of the clone selection process and the negative selection process by means of analogy similarity. This method is applied in an IDS （Intrusion Detection System） following several steps. Firstly, the initial abnormal behaviours sample set is optimized through the combining of the AIS （Artificial Immune System） and the genetic algorithm. Then, the abnormity probability algorithm is raised considering the two sides of abnormality and normality. Finally, an intrusion detection system model is established based on the above algorithms and models.