摘要
大型网络的入侵检测主要采用多个分布式代理(Agent).这些代理具有一定的智能以便处理各种入侵.文章提出用贝叶斯网络构造各Agent,这样的Agent具有学习、快速识别和对不完备数据集的处理能力,从而使系统具有更好的适应性.最后用一实倒来说明贝叶斯网络在入侵检测领域内的应用.
Intrusion Detection in a large network mainly rely on the use of many distributed agents. Agents should have a kind of artificial intelligence in order to cope successfully with different intrusion cases. In this paper, we suggest that all agents are constructed with Bayesian network. Its capabilities of learning, quick identification and processing of insufficient data sets can be used in intrusion detection, so that the system constructed is highly adaptive. Finally an experimental study is presented to indicate the applications of Bayesian network in intrusion detection.
出处
《小型微型计算机系统》
CSCD
北大核心
2003年第5期913-915,共3页
Journal of Chinese Computer Systems
基金
国家自然科学基金(69973020)资助
国防科工委应用基础基金资助(J1300D004)
