Dynamic Probabilistic Packet Marking Based on PPM

Bo Feng, Guo Fan, Yu Min
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引用次数: 8

Abstract

Most of the probability of packet marking(PPM) have existed many problems such as the lost of marking information, the difficulties to reconstruct attack path, low accuracy and so on. In this work, we present a new approach, called dynamic probabilistic packet marking (DPPM), to further improve the effectiveness o fPPM. Instead of using a fixed marking probability, we propose to judge whether the packet has been marked or not then choose a proper marking probability. DPPM may solve most of the problems in PPM method. Formal analysis indicates that DPPM outperforms PPM in most aspects.
基于PPM的动态概率分组标记
大多数包标记概率算法存在标记信息丢失、攻击路径重构困难、准确率低等问题。在这项工作中,我们提出了一种新的方法,称为动态概率分组标记(DPPM),以进一步提高fPPM的有效性。我们不使用固定的标记概率,而是先判断数据包是否被标记,然后选择合适的标记概率。DPPM可以解决PPM法中的大部分问题。形式分析表明,DPPM在大多数方面都优于PPM。
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