Intrusion Detection System based on combination of expert system and Bp neural network

Liang Zhou, Lixin Ke, K. Wu, Xitao Zheng
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Abstract

This paper aims to study the application of expert system combined with neural network in Intrusion Detection System. It brings improvement to BP algorithm of neural networks, meanwhile a series of rule sets have been created using the experience and knowledge from experts, scholars as well as professional forecasters. This benefits the simulation of human expert reasoning of the decision-making process and helps the judgments to create an expert system. Test shows improved efficiencies in intrusion detection than those with single BP algorithm.
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基于专家系统和Bp神经网络相结合的入侵检测系统
本文旨在研究专家系统与神经网络相结合在入侵检测系统中的应用。它对神经网络的BP算法进行了改进,同时利用专家、学者和专业预测员的经验和知识创建了一系列规则集。这有利于模拟人类专家对决策过程的推理,并有助于建立专家系统的判断。测试结果表明,与单一BP算法相比,入侵检测效率有所提高。
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