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Novel intrusion detection system integrating layered framework with neural network

机译:结合分层框架与神经网络的新型入侵检测系统

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The threat from spammers, attackers and criminal enterprises has grown with the expansion of Internet, thus, intrusion detection systems (IDS)have become a core component of computer network due to prevalence of such threats. In this paper, we present layered framework integrated with neural network to build an effective intrusion detection system. This system has experimented with Knowledge Discovery & Data Mining(KDD) 1999 dataset. The systems are compared with existing approaches of intrusion detection which either uses neural network or based on layered framework. The results show that the proposed system has high attack detection accuracy and less false alarm rate.
机译:垃圾邮件发送者,攻击者和犯罪企业的威胁随着Internet的扩展而增长,因此,入侵检测系统(IDS)由于这种威胁的普遍性而已成为计算机网络的核心组成部分。在本文中,我们提出了与神经网络集成的分层框架,以构建有效的入侵检测系统。该系统已经试验了知识发现和数据挖掘(KDD)1999数据集。将该系统与使用神经网络或基于分层框架的现有入侵检测方法进行了比较。结果表明,该系统具有较高的攻击检测精度和较低的误报率。

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