计算机应用与软件Issue(2)：294-298,5.DOI:10.3969/j.issn.1000-386x.2016.02.068
基于树加权朴素贝叶斯算法的入侵检测技术研究
INTRUSION DETECTION TECHNOLOGY BASED ON TREE-WEIGHTING NAIVE BAYESIAN ALGORITHM
摘要
Abstract
Aiming at the deficiency of naive Bayesian (NB)algorithm in the reality,this paper proposes an improved NB algorithm which is called tree-weighting naive Bayesian (TW-NB)algorithm.This algorithm,by introducing the decision tree induction (DTI),selects a comparatively more important subset of attributes from the set of conditional independence assumption,and uses weighting parameter to weaken the conditional independence assumption of naive Bayesian and thus reduces the dimensionality of the classification data,as well as improves the classification accuracy of the algorithm.It is verified by combining the experimental results that the intrusion detection technology based on the TW-NB algorithm can achieve higher detection rates (DR)and lower false rates (FR)for different network intrusion types when the computational resources used are limited.关键词
朴素贝叶斯/决策树归纳法/入侵检测/准确率Key words
Naive Bayesian/DTI/Intrusion detection/Accuracy分类
信息技术与安全科学引用本文复制引用
王辉,陈泓予,杨姗姗..基于树加权朴素贝叶斯算法的入侵检测技术研究[J].计算机应用与软件,2016,(2):294-298,5.基金项目
国家自然科学基金项目（51174263）；教育部博士点基金项目（20124116120004）；河南省教育厅科学技术研究重点项目（13A510325）。 （）
