基于人工免疫系统的检测器生成算法改进

Improved Generation Algorithm for the Detector Based on the Artificial Immune Theory

研究了免疫检测器的生成机制,通过采用k平均聚类算法提取到的规则生成未成熟检测器,提出了将模糊逻辑理论运用到成熟检测器激活及记忆检测器生成的进化方法,改进了传统的以人工免疫为基础的入侵检测系统中随机生成未成熟检测器的算法.实验表明该方法能够提高检测器的检测性能,证实了该算法的有效性.

The paper studied the generative mechanism of immune detectors. The rules obtained from k - means clustering algorithm are used to produce the immature detector. It proposed the method for activating the mature detector, which improved the memory detector according to the fuzzy logic theory. It improved the traditional algorithm of randomly generating immune detector in the intrusion detection system based on artificial immune. Experiments showed that this method could improve the detection performance of the detectors, a confirmation of the effectiveness of the algorithm.