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A memory-efficient parallel string matching for intrusion detection systems

机译:用于入侵检测系统的内存有效并行字符串匹配

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摘要

As the variety of hazardous packet payload contents increases, the intrusion detection system (IDS) should be able to detect numerous patterns in real time. For this reason, this paper proposes an Aho-Corasick algorithm based parallel string matching. In order to balance memory usage between homogeneous finite-state machine (FSM) tiles for each string matcher, an optimal set of bit position groups is determined. Target patterns are sorted by binary-reflected gray code (BRGC), which reduces bit transitions in patterns mapped onto a string matcher. In the evaluations of Snort rules, the proposed string matching outperforms the existing bit-split string matching.
机译:随着危险数据包有效载荷内容的多样性增加,入侵检测系统(IDS)应该能够实时检测大量模式。为此,本文提出了一种基于Aho-Corasick算法的并行字符串匹配。为了在每个字符串匹配器的同类有限状态机(FSM)磁贴之间平衡内存使用,确定了一组最佳的位位置组。目标模式通过二进制反射格雷码(BRGC)进行排序,这减少了映射到字符串匹配器的模式中的位转换。在Snort规则的评估中,建议的字符串匹配优于现有的位拆分字符串匹配。

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