基于软计算技术集成的入侵检测系统

Xiaolong Xu, Zhonghe Gao, Lijuan Han
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摘要

软计算技术越来越广泛地应用于解决各种实际问题。本文将不同软计算技术的集成应用于入侵检测系统。随着网络攻击事件的不断增多,构建有效的入侵检测系统势在必行,但也面临着巨大的挑战。研究了两种软计算技术:人工神经网络和支持向量机。实验结果表明,人工神经网络与支持向量机相结合的入侵检测方法在分类精度上优于单个入侵检测方法。
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Intrusion Detection System Based on Integration of Soft Computing Techniques
Soft computing techniques are more and more widely used to solve a variety of practical problems. This paper applied the integration of different soft computing techniques in intrusion detection system(IDS). Due to the increasing incidents of network attacks, building effective intrusion detection system is necessary, but it faces great challenges. Two sorts of soft computing techniques are studied:Artificial Neural Network (ANN) and Support Vector Machines(SVM). Experimental results show that integration of ANN and SVM is superior to individual approaches for intrusion detection in terms of classification accuracy.
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