Distributed intrusion detection systems( DIDS) have many advantages such as scalability, subversion resistance.
分布式入侵检测系统有许多优点，如可测量性和抗破坏性。
This mechanism has a perfect scalability and is well fitted to the characteristic of large-scale distributed intrusion detection systems.
文中提出的数据融合机制具有很好的扩展性，非常适合大规模分布式网络环境的特点。
Based on D-S evidence theory in data fusion technology, this paper applies it to distributed intrusion detection systems and gives a network intrusion early warning model.
本文以数据融合技术中的D -S证据理论为基础，将其运用于分布式入侵检测系统中，提出了基于D - S证据理论的网络入侵预警模型。
To solve the problem of lacking dynamic organizing agility in distributed intrusion detection systems, an on-demand intrusion detection model adaptive to the Shared data environment was presented.
为了解决分布式入侵检测系统缺乏动态组织敏捷性的问题，提出了适应数据网格的按需入侵检测模型。
To solve the problem of lacking dynamic organizing agility in distributed intrusion detection systems, an on-demand intrusion detection model adaptive to the Shared data environment was presented.
为了解决分布式入侵检测系统缺乏动态组织敏捷性的问题，提出了适应数据网格的按需入侵检测模型。
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