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Distributed and Cooperative Multi-agent Based Intrusion Detection System

机译:基于分布式协作多智能体的入侵检测系统

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One of the primary challenges in intrusion detection is modeling typical application behavior, so that we can recognize attacks by their atypical effects without raising too many false alarms. IDS implemented using mobile agents is one of the new paradigms for intrusion detection. In this paper, we have proposed an effective intrusion detection system in which local agent collects data from its own system and it classifies anomaly behaviors using SVM classifier. Each local agent is capable of removing the host system from the network on successful detection of attacks. The mobile agent gathers information from the local agent before it allows the system to send data. Our system identifies successful attacks from the anomaly behaviors. Experimental results show that the proposed system has high detection rate and low false alarm rate which encourages the proposed system.
机译:入侵检测的主要挑战之一是对典型的应用程序行为进行建模,以便我们能够通过其非典型效应来识别攻击,而不会引发太多错误警报。使用移动代理实现的IDS是入侵检测的新范例之一。在本文中,我们提出了一种有效的入侵检测系统,其中本地代理从其自身的系统收集数据,并使用SVM分类器对异常行为进行分类。每个本地代理都能够在成功检测到攻击后从网络中删除主机系统。移动代理在允许系统发送数据之前先从本地代理收集信息。我们的系统从异常行为中识别出成功的攻击。实验结果表明,所提出的系统具有较高的检测率和较低的误报率,这对所提出的系统具有鼓励作用。

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