基于双层防护体系结构的人工免疫模型  

Artificial Immune Model Based on Double Protecting System

作　　者：符海东[1] 袁细国[1] 

机构地区：[1]武汉科技大学计算机科学与技术学院,武汉430081

出　　处：《计算机工程》2008年第1期178-180,共3页Computer Engineering

基　　金：湖北省教育厅重点科研基金资助项目(2004D006)

摘　　要：低效率检测能力的免疫模型不能满足当今网络入侵检测的需要,该文提出一个双层防护体系结构,将免疫原理和模糊数学理论相结合,具有2次检测过程。该模型利用了模糊模式识别理论对数据样本进行数据浓缩,从给定学习样本数据中提取一组规则作为检测的重要依据。实验表明,该模型可以有效降低漏报率及误报率,具有较大的参考价值,在实际中有良好的应用前景。The immune model with low detection efficiency can not adapt to the current network intrusion detection. This paper presents an improved immune model based on double protecting system, combing the biological immune theory with the fuzzy mathematics principle, with two detection processes. According to the Fuzzy Pattern Recognition （F-PR）, some useful data samples are condensed, and a rule is abstracted from the special data sample as important evidence for detection. Experimental results show that this model can achieve low false alarm rate and missing rate.

关 键 词：入侵检测 人工免疫 模糊模式识别 

分 类 号：TP393.08[自动化与计算机技术—计算机应用技术]