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An Anomaly Intrusion Detection Method Based on Improved K-Means of Cloud Computing

机译:基于改进的云计算K均值的异常入侵检测方法

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With the widely use of cloud computing, security issues become increasingly important. In the scene of cloud computing, traditional intrusion detection methods are not practical. In this paper, a new intrusion detection method based on improved K-means is proposed, which is designed to fit the characteristics and security requirements of cloud computing. The method provides a clustering algorithm and a distributed intrusion detection method based on it. The new method can find out known attack as well as anomaly attack in the environment of cloud computing. The result of simulate test proves that the new method can decrease the false positive and false negative rate, and accelerate the speed of intrusion detection.
机译:随着云计算的广泛使用,安全问题变得越来越重要。在云计算领域,传统的入侵检测方法不切实际。本文提出了一种基于改进的K-means的入侵检测新方法,旨在适应云计算的特点和安全性要求。该方法提供了聚类算法和基于该聚类算法的分布式入侵检测方法。新方法可以发现云计算环境中的已知攻击以及异常攻击。仿真测试结果表明,该方法可以降低误报率和误报率,加快入侵检测速度。

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