%0 Journal Article
%T Using Clustering to Improve Self-Purity of Dynamic Clonal Selection Algorithm<br>利用聚类改进动态克隆选择算法的自体纯净性问题
%A XIAO Jun-Bi
%A JI Cui-Cui
%A <br>肖军弼
%A 季翠翠
%J 计算机系统应用
%D 2010
%I 
%X In the intrusion detection process of dynamic clonal selection algorithm, the antigens detected by memory detectors and maturity detectors are directly considered as self immature detectors to be tolerated. But there may be new attacks hidden in these antigens. To solve this problem, a new idea with clustering analysis is proposed. The clustering algorithm cluster remaining antigens then analyzes data existing in small cluster, finds hidden attacks and update memory detector set in time. The experimental results show that the dynamic clonal selection algorithm with clustering analysis can enhance the detection system's ability to discover unknown intrusions.
%K dynamic clonal selection algorithm
%K instrusion detection
%K remaining antigen
%K cluster analysis<br>动态克隆选择算法
%K 入侵检测
%K 剩余抗原
%K 聚类
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=4ECF2338619DEA0EB80BCCB7B0F8D8DB&yid=140ECF96957D60B2&vid=2A8D03AD8076A2E3&iid=94C357A881DFC066&sid=73579BC9CFB2D787&eid=DABEF202280E7EF1&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=5