基于多智能体的智能入侵检测系统设计

Xiaodong Zhu, Zhiqiu Huang, Hang Zhou
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引用次数: 23

摘要

针对某部门员工利用局域网络和上位机滥用特权谋取私利的情况,本文提出了一种基于多代理的入侵检测系统MAIIDS (multi-agent based intelligent intrusion detection system)。该模型中的学习代理模块可以通过人工神经网络、关联规则等多种数据挖掘技术,自调整地学习基于网络的审计数据和基于主机的审计数据。学习代理生成规则,检测代理根据这些规则检测审计数据并做出响应。大量实验表明,该系统具有很高的自适应能力、智能化和可扩展性。目前MAIIDS已应用于多个安全部门,并获得了良好的口碑
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Design of a Multi-agent Based Intelligent Intrusion Detection System
Considering some employees in the department abuse their privilege for personal gain through the local network and the host computer, in this paper, we present a multi-agent based intrusion detection system named MAIIDS (multi-agent based intelligent intrusion detection system). The learning agent module in this model can self-adjustingly learn network based audit data and host based audit data with more than one technique of data mining, such as the artificial neural network, the association rules and so on. The learning agent can produce rules, and the detection agent can detect audit data according to these rules and response to them. A lot of experiments indicate that this system has very high self-adapting ability, intelligence, and expansibility. Now MAIIDS has been applied to several security departments and has received good reputation
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