%0 Journal Article
%T Research of Network Intrusion Detection Model Based on Artificial Immune<br>基于人工免疫的网络入侵检测模型的研究
%A ZHANG Yu-fang
%A XIONG Zhong-yang
%A SUN Gui-hu
%A LAI Su
%A ZHAO Yin
%A <br>张玉芳
%A 熊忠阳
%A 孙桂华
%A 赖苏
%A 赵鹰
%J 计算机科学
%D 2009
%I 
%X Aiming at limitation of existent network intrusion detection model with artificial immune idea, an improved network intrusion detection model based on dynamic clonal selection algorithm was presented. For accelerating normal IP packets access, the self-pattern class was proposed and most of self-antigens were filtered and amended the self-antigen set dynamically in detection process. The constraint based detectors were adopted as antibody, any-r intervals mat ching rule was used to determinant antibody and antigen, and split detector method were settled to self-antigen mat ching. The experimental results show that the proposed model can achieve a faster running speed, the better detecting rates,and adapt to dynamically changing environments.
%K Intrusion detection
%K Artificial immune
%K Antibody
%K Antigen<br>入侵检测
%K 人工免疫
%K 抗体
%K 抗原
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=64A12D73428C8B8DBFB978D04DFEB3C1&aid=2B22C687A788E69FCEAE4BD2DED044C9&yid=DE12191FBD62783C&vid=933658645952ED9F&iid=59906B3B2830C2C5&sid=6270DC1B5693DDAF&eid=4DB1E72614E68564&journal_id=1002-137X&journal_name=计算机科学&referenced_num=0&reference_num=9