软件
軟件
연건
computer engineering & Software
2015年
9期
48-51
,共4页
入侵检测%数据挖掘%关联%聚类
入侵檢測%數據挖掘%關聯%聚類
입침검측%수거알굴%관련%취류
Intrusion detection%Data mining%Association%Clustering
针对当前入侵检测系统的局限性，提出将数据挖掘技术引入到入侵检测中，研究了Apriori关联算法、ID3分类算法和 FHCAM 聚类算法在入侵检测中的应用，建立了一个基于数据挖掘的自适应入侵检测模型。该模型能够识别已知和未知的入侵，降低检测的漏报率和误报率，有效的提高检测效率。
針對噹前入侵檢測繫統的跼限性，提齣將數據挖掘技術引入到入侵檢測中，研究瞭Apriori關聯算法、ID3分類算法和 FHCAM 聚類算法在入侵檢測中的應用，建立瞭一箇基于數據挖掘的自適應入侵檢測模型。該模型能夠識彆已知和未知的入侵，降低檢測的漏報率和誤報率，有效的提高檢測效率。
침대당전입침검측계통적국한성，제출장수거알굴기술인입도입침검측중，연구료Apriori관련산법、ID3분류산법화 FHCAM 취류산법재입침검측중적응용，건립료일개기우수거알굴적자괄응입침검측모형。해모형능구식별이지화미지적입침，강저검측적루보솔화오보솔，유효적제고검측효솔。
To solve the problems of current intrusion detection systems, the methods and technologies of data mining are applied to intrusion detection. The Apriori algorithm, the ID3 algorithm and the FHCAM algorithm are re-searched for application to intrusion detection, an adaptive model of intrusion detection based on data mining is estab-lished. This model can recognize known or unknown intrusions of the network and decrease the false detection rate of the intrusion detection, so the efficiency of all kinds of intrusion detection is improved.
