一种基于模糊免疫的检测器生成算法

A Detector Algorithm based on Fuzzy Immune

网络入侵方法和网络环境的不断变化,入侵越来越难以防范和检测。针对当前入侵检测过程中检测器生成问题,提出了一种基于生物免疫机制和模糊理论的检测器生成算法。该算法利用改进的否定选择算法来提高生成的检测器为成熟检测器的概率。通过仿真实验,表明该模型有效地改善了系统的性能,大大减少了不可避免的"黑洞"数量,黑洞数量大幅下降,检测率有显著提高。

The changes of network environment and Internet intrusion methods cause the intrusion more difficult to detect and prevent. This paper proposes a detector algorithm based on the biological immune mechanisms and fuzzy theories aiming at the questions of detector formation in the process of intrusion detection. This algorithm, with improved negative selection algorithm, can increase the rate of mature detectors that has been generated. Through the simulation experiment, this algorithm improves effectively the performance of system, reduces greatly the amounts of unavoidable threshold of matching holes, and raises the detected rate.