基于人工免疫的记忆检测器研究

Memory Detector Research Based on Artificial Immune Theory

传统的手段已不能充分地解决计算机网络的安全问题。为了确保计算机网络系统安全,建立一个有效的入侵检测系统IDS,针对IDS中成熟检测器检测率低和错误肯定率高的问题,根据人工免疫记忆原理,研究了免疫检测器集中成熟检测器激活,记忆检测器生成与变异机制以及演化,给出了记忆检测器生成算法,研究了记忆检测器变异和淘汰机制。实验结果证明记忆检测器为主的检测器集合实现了检测器自学习和联想记忆的功能,提高了入侵检测系统的自适应能力和检测率,减少了错误肯定率。

Conventional means haven＇ t already been able to resolve the security problem of computer network, for ensuring computer network system security, and founding an effective intrusion detection system, aiming at mature detector inefficiencies and the high rate of errors sure problem. Under artificial immune theory, research immunoassay mature detector activation, memory detectors generation and variation mechanism and evolution, put forward the memory detectors generation algorithm, study thc memory detectors variation and elimination mechanism. Experimental results show the main memory detectors of the detector set achieve a self - learning dctectors and associative memory function, enhanced intrusion detection system and the adaptive ability of detection rate and reduce the rate of errors sure.