基于特征值的阴性选择算法和MHC检测滤窗  

Negative Selection Algorithm and MHC Detecting Window Based on Eigenvalue Set

作　　者：徐锐[1] 马文丽[1,2] 郑文岭[1,2] 

机构地区：[1]上海大学电子生物技术研究中心,上海200072 [2]广州南方医科大学基因工程研究所,广东广州510515

出　　处：《中北大学学报（自然科学版）》2011年第3期296-302,共7页Journal of North University of China(Natural Science Edition)

基　　金：国家自然科学基金资助项目(39880032);广东省自然科学基金资助项目(5004737);广州市重大科技项目(199-2005-001)

摘　　要：在分析连续位匹配规则基础上提出了特征值匹配的概念,通过对特征值比较代替传统匹配方式,实现了阴性算法的改进.引入主要组织相容复合体(Major Histocompatibility Complex,MHC)特征判别概念,在分析黑洞特性以及与非检测器集合关系的基础上,设计MHC检测滤窗作为检测器之后的更高级别安全防护层,以彻底杜绝黑洞模式的侵入,真正意义上消除黑洞这一危险检测漏洞.仿真结果表明,使用MHC独立检测滤窗成功地发现了所有检测器未能阻击的黑洞模式,确保了外来模式检测的准确性和安全性,而其检测时间和对系统资源的占用并未因此而显著增加.The concept of eigenvalue matching was put forward based on analyzing the continuous bits matching rule. The negative algorithm was improved by eigenvalue matching rule. The conception of major histocompatibility complex（MHC） was introduced, and the MHC detecting window was designed based on analyzing the characteristic of black holes and the relationship between non-detector set and black holes to terminating the threat of black holes. Simulation results show that the black holes which can＇t be found using detectors were successfully detected by this new detecting window, which ensured the precision and security of the detecting system. Also, the consumption of the time and occupation of system resource were not increased significantly.

关 键 词：免疫原理 阴性选择 特征值 黑洞 主要组织相容复合体 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]