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    王勇, 杨辉华, 王行愚, 何倩. 一种基于进化神经网络的入侵检测实验系统[J]. 华东理工大学学报(自然科学版), 2005, (3): 362-366.
    引用本文: 王勇, 杨辉华, 王行愚, 何倩. 一种基于进化神经网络的入侵检测实验系统[J]. 华东理工大学学报(自然科学版), 2005, (3): 362-366.
    An Intrusion Detection Experimental System Using Evolutionary Neural Network[J]. Journal of East China University of Science and Technology, 2005, (3): 362-366.
    Citation: An Intrusion Detection Experimental System Using Evolutionary Neural Network[J]. Journal of East China University of Science and Technology, 2005, (3): 362-366.

    一种基于进化神经网络的入侵检测实验系统

    An Intrusion Detection Experimental System Using Evolutionary Neural Network

    • 摘要: 参照MIT Lincoln实验室的入侵检测实验方案,建立了一个基于Linux主机的入侵检测实验环境,提出了相应的入侵特征选择方案,并应用进化神经网络检测入侵,实现了对多种攻击的实时特征抽取及检测。实验表明:系统设计合理,特征抽取及检测方法有效,能较好地检测已知和未知入侵。

       

      Abstract: Complying with the basic rules set by MIT Lincoln Lab's IDS test, this paper establishes a Linux-host-based intrusion detection experimental system (IDS), and puts forward a feasible intrusion feature set. The IDS system takes evolutionary neural networks as decision-making tool, and extracts 29 features and detects real-time intrusions. The experiment results demonstrate that the detection system is reasonably designed, the extracted features are effective, and the IDS system can detect most known and unknown attacks.

       

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