基于重尾特性的随机扫描蠕虫检测

Yufeng Cheng, Yabo Dong, Dongming Lu, Yunhe Pan, Zhengtao Xiang
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引用次数: 2

摘要

蠕虫检测系统必须对蠕虫进行高效、有效的检测。目前的检测方法主要是基于蠕虫连接成功率低的特性。但是,如果蠕虫故意插入成功的连接,它们可能会忽略蠕虫。由于正常TCP连接的数据包或字节大小是重尾的,我们提出了一种结合失败连接检测标准和给定本地主机连接大小的重尾分布的检测方法。蠕虫更难躲避。该方法可降低假阴性和假阳性率。实验结果表明,该方法能够高效、有效地检测出扫描蠕虫。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Detecting randomly scanning worms based on heavy-tailed property
Worm detection system must detect worms efficiently and effectively. Current detection methods are mainly based on the property of low successful connections rate of worms. However, they may neglect worms if worms insert successful connections deliberately. Because the size in packets or bytes of normal TCP connections is heavy-tailed, we present a detection method by combining detection criteria of failed connections and heavy-tailed distribution of connection size for a given local host. It is more difficult for worms to evade. The method can decrease false negative and positive rates. The experiments show that our method can detect scanning worms with high efficiency and effectiveness.
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