Network Traffic Abnormality Detection Algorithm Based on Self-adaptive Threshold
Network Traffic Abnormality Detection Algorithm Based on Self-adaptive Threshold
复制标题
基于自适应阈值的网络流量异常检测算法
DOI：
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发表时间：
2009
期刊：
影响因子：
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通讯作者：
Wu Xi
中科院分区：
文献类型：
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作者：
Wu Xi
大多数异常流量检测算法都采用固定阈值，但这些方法不能清晰地描述网络行为。本文提出了一种自适应阈值残差率检测方法，该方法引入了刷新机制，该机制混合了前一次的行为，得到一个动态阈值作为判断规则。该方法还设置了一个插值以准确地描述网络行为。通过实验验证了该方法的有效性和性能的先进性。
Most of abnormal traffic detection algorithms use fixed threshold,but these methods cannot describe action of network clearly.This paper presents an self-adaptive threshold residual ratio detection method which introduces the refreshing mechanism.The mechanism mixes action of previous time and gets a dynamic threshold which can act as judge rule.The method also sets an interpose in order to depict network action exactly.The paper does experiment to validate the validity and advance in performance of this method.