To solve the distributed attacks efficiently, this paper presents the Distributed Intrusion Detection Model Based on Multisensor Data Fusion and Mining (DIDM).
为有效解决分布式攻击,提出了基于多传感器数据融合与挖掘的分布式入侵检测模型。
By applying Multisensor Data Fusion and Data Mining to intrusion detection, DIDM provides the comprehensive assessment of network attack and defense situations continuously and globally.
将多传感器数据融合与数据挖掘技术应用到分布式入侵检测中,可连续和全面地提供网络攻防战场环境态势的综合评估。
By applying Multisensor Data Fusion and Data Mining to intrusion detection, DIDM provides the comprehensive assessment of network attack and defense situations continuously and globally.
将多传感器数据融合与数据挖掘技术应用到分布式入侵检测中,可连续和全面地提供网络攻防战场环境态势的综合评估。
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