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基于密度的异常挖掘智能网络入侵检测系统设计与实现
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2009-07-30
陆军航空兵
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论文提出了基于密度的异常挖掘新方法，并将其应用于入侵检测系统引擎设计中，构
建了相应的网络入侵检测系统。该系统通过挖掘异常数据的高效性，可及时发现新的未知入侵行为，用以更新入侵规则库。基于该规则库，系统采用BM 模式匹配算法进行实时入侵检测。论文运用形式化语言对入侵检测系统各子模块进行结构化分析与描述。
关键词：异常挖掘；密度；入侵检测
Abstract：The paper puts forward a new method of density-based anomaly data mining, the
method is used to design the engine of network intrusion detection system (NIDS), thus a new IDS is constructed based on the engine. The NIDS can find new unknown intrusion behaviors, hich are used to updated the intrusion rule-base, based on which intrusion detections can be arried out online by the BM pattern match algorithm. Finally all modules of the NIDS are escribed by formalized language.
Key words：Outliers mining；Density；Intrusion detection
建了相应的网络入侵检测系统。该系统通过挖掘异常数据的高效性，可及时发现新的未知入侵行为，用以更新入侵规则库。基于该规则库，系统采用BM 模式匹配算法进行实时入侵检测。论文运用形式化语言对入侵检测系统各子模块进行结构化分析与描述。
关键词：异常挖掘；密度；入侵检测
Abstract：The paper puts forward a new method of density-based anomaly data mining, the
method is used to design the engine of network intrusion detection system (NIDS), thus a new IDS is constructed based on the engine. The NIDS can find new unknown intrusion behaviors, hich are used to updated the intrusion rule-base, based on which intrusion detections can be arried out online by the BM pattern match algorithm. Finally all modules of the NIDS are escribed by formalized language.
Key words：Outliers mining；Density；Intrusion detection
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