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An efficient entropy-based network anomaly detection method using MIB

机译:基于MIB的基于熵的高效网络异常检测方法

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With the increasingly widespread application of computer network, it has become a critical task to detect anomalous behaviors in the field of network security. In this paper we develop an entropy-based statistical approach that determines and reports entropy contents for variables in the Management Information Base. The change of the entropy value indicates that a massive network event or an anomaly may occur. We give the analysis on a real data set provided by a large-size network company. Both our theoretical analysis and experimental results demonstrate that the method is effective and efficient for network anomaly detection.
机译:随着计算机网络的日益广泛的应用,检测网络安全领域中的异常行为已成为一项关键任务。在本文中,我们开发了一种基于熵的统计方法,该方法确定并报告“管理信息库”中变量的熵内容。熵值的变化指示可能发生大规模网络事件或异常。我们对大型网络公司提供的真实数据集进行分析。我们的理论分析和实验结果均表明该方法对于网络异常检测是有效且高效的。

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