基于规则重组的“非我”特征序列抽取算法  

Nonself Feature Extracting Algorithm Based on Rules Reorganization

作　　者：王凤先[1] 刘振鹏[1] 潘洪涛[1] 

机构地区：[1]河北大学数学与计算机科学学院,河北保定071002

出　　处：《计算机工程与应用》2006年第14期146-148,共3页Computer Engineering and Applications

摘　　要：抽取“非我”分类特征序列并依据它对“非我”进行准确分类是计算机免疫系统实现高效免疫应答的关键。基于规则重组的“非我”分类特征抽取算法(NFERR)以进程的系统调用序列为数据源,利用机器学习和数据挖掘方法抽取分类规则,并根据与原系统调用序列的匹配结果对这些规则进行重组得到“非我”特征序列。实验结果证明了此算法在“非我”分类特征抽取上的有效性。It is pivotal for the efficient immune responsion implement in computer immune system that extracting ＂nonself＂ classfic feature sequences and classfic ＂noself＂ acurrately.NFERR extracts nonself classfy rules using algrithm of machine learning and data mining from system call sequences which is as data source,then reorganizes these rules according to the match result to get the nonself feature sequences.The experiment result shows the availability and efficiency of NFERR.

关 键 词：计算机免疫 数据挖掘 “非我”分类特征 

分 类 号：TP311.13[自动化与计算机技术—计算机软件与理论]