模糊关联规则挖掘算法及其在异常检测中的应用

熊平, 朱天清, 黄天戍

熊平, 朱天清, 黄天戍. 模糊关联规则挖掘算法及其在异常检测中的应用[J]. 武汉大学学报 ( 信息科学版), 2005, 30(9): 841-845.
引用本文: 熊平, 朱天清, 黄天戍. 模糊关联规则挖掘算法及其在异常检测中的应用[J]. 武汉大学学报 ( 信息科学版), 2005, 30(9): 841-845.
XIONG Ping, ZHU Tianqing, HUANG Tianshu. Algorithm of Mining Fuzzy Associate Rules in Anomaly Detection[J]. Geomatics and Information Science of Wuhan University, 2005, 30(9): 841-845.
Citation: XIONG Ping, ZHU Tianqing, HUANG Tianshu. Algorithm of Mining Fuzzy Associate Rules in Anomaly Detection[J]. Geomatics and Information Science of Wuhan University, 2005, 30(9): 841-845.

模糊关联规则挖掘算法及其在异常检测中的应用

基金项目: 国家公安部科研基金资助项目(200342-823-01)
详细信息
    作者简介:

    熊平,博士生,主要研究方向为网络安全

  • 中图分类号: TP393

Algorithm of Mining Fuzzy Associate Rules in Anomaly Detection

  • 摘要: 阐述了在入侵检测中应用模糊关联规则挖掘的方法,提出了对传统Apriori算法的改进。最后以网络流量分析为例,详细描述了在入侵检测中运用模糊关联规则挖掘的步骤,并以规则集相似度建立对入侵的响应机制。
    Abstract: An algorithm of mining fuzzy association rules is presented on the basis of improving the classic association rules mining algorithm-Apriori to solve the problem "sharp boundary". In the algorithm, each quantitative attribute is replaced by a fuzzy set and divided into several attributes, which are calculated as separate attributes of database in mining fuzzy associate rules. The process of applying the approach in anomaly detection is discussed in detail. Using experiments on network traffic analysis, the feasibility of applying the mining fuzzy associate rules in intrusion detection is validated.
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出版历程
  • 收稿日期:  2005-05-21
  • 修回日期:  2005-05-21
  • 发布日期:  2005-09-04

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