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    一种基于交互式知识发现的入侵事件关联方法研究

    Study of an Intrusion Event Correlation Method Based on Interactive Knowledge Discovery

    • 摘要: 分析了入侵检测系统的现存问题 ,总结了入侵事件关联系统的最新进展和缺陷 ,提出一个基于人机交互式知识发现的入侵事件关联系统 该系统离线部分在入侵事件关联领域首次引入FPTree和WINEPI算法进行交互式知识发现 ,并将发现的频繁模式和序列模式转化成入侵事件关联规则 ;在线部分利用先验知识和交互式知识发现的关联知识 ,以嵌入式CLIPS推理组件作为推理引擎 ,对多个入侵检测器上报的事件进行高效关联和归并 在集成化网络安全监控及防卫系统Net Keeper中的实际应用表明本系统是一个开放、高效的入侵事件关联平台

       

      Abstract: On the basis of analyzing the evolution and drawbacks of current intrusion detection systems(IDS), a novel intrusion event correlation system(ECS) based on interactive knowledge discovery is proposed. ECS is composed of off-line part and on-line part. As the former, FP Tree and WINEPI algorithms are first introduced to implement interactive knowledge discovery for intrusion events correlation. And the discovered frequent patterns and sequence patterns are converted into associative rules for the inference of intrusion events. As the online part of the ECS, embedded CLIPS inference engine is employed to do event correlation, based on priori knowledge and the associative rules discovered above. Application of the ECS in the integrated network security monitor and defense system named Net-Keeper shows that the proposed system is an open and efficient intrusion event correlation engine.

       

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