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A Synergetic Pattern Matching Method Based-on DHT Structure for Intrusion Detection in Large-scale Network

机译:基于DHT结构在大型网络中入侵检测的协同模式匹配方法

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摘要

Research in network security, with the attacks becoming more frequent, increasing complexity means, for the large-scale network intrusion detection, this paper presents a warning by analyzing the behavior of the log, the contents of the relevant association, through the DHT(Distributed Hash Table) distributed architecture, the Collabarative matching, fusion, and ultimately determine the method of attack paths. First, by improving the classical Apriori algorithm, greatly improving the efficiency of the association. At the same time, through the behavior pattern matching algorithms to extract information about the behavior of the alert and the behavior sequence elements to match the template, and through the right path to finally determine the value of the threat of the network path. After the design of a DHT network, the distributed collaborative match the path used to find complex network attacks. Finally, the overall algorithm flow, proposed a complete threat detection system architecture.
机译:网络安全的研究,随着攻击更频繁,复杂性意味着大规模的网络入侵检测,通过分析日志的行为,通过DHT(分布式)分析了日志的行为,提出了警告哈希表)分布式架构,合法匹配,融合,最终确定攻击路径的方法。首先,通过提高经典的APRIORI算法,大大提高了关联的效率。同时,通过行为模式匹配算法提取有关警报行为的信息和行为序列元素以匹配模板,并通过右路最终确定网络路径威胁的值。在设计DHT网络之后,分布式协作匹配用于查找复杂网络攻击的路径。最后,整体算法流程,提出了完整的威胁检测系统架构。

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