摘要
入侵检测技术越来越受到人们的关注。提出了一种用于入侵检测中警报分类的改进自适应贝叶斯算法,该算法减少了入侵检测中的积极错误。通过对标准数据测试集KDD99进行实验,证明了此方法在短应答时间里拥有极高的分类效率,而且只需要极少的计算资源来减少积极错误。
Intrusion Detection has received more and more attention.Proposed a improved self adaptive Bayesian algorithm to the alert classification and reduce false positives in Intrusion Detection.By the experiment on KDD99 benchmark dataset,it is proved that this method has high classification rates in short response time and reduce false positives using limited computational resources.
出处
《软件》
2011年第3期113-115,120,共4页
Software
关键词
异常入侵检测
报警分类
贝叶斯算法
积极错误
anomaly intrusion detection
alert classification
Bayesian algorithm
false positives
