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Packet signature mining for application identification using an improved Apriori algorithm

机译:使用改进的Apriori算法进行数据包签名挖掘以识别应用程序

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Extracting packet signatures automatically and accurately are the foundation of traffic identification for most network monitoring and forensics application. The Apriori algorithm is a common and useful method to fulfill the task. For huge amount Internet traffic, the traditional Apriori algorithm, produce huge candidate itemsets and will occupy large I/O costs in scanning database. An improvement method is proposed in this paper. Based on the pruning to the candidate and the public signature database, it dynamically reduced the number of the scanning itemsets to make the scanning efficient. The experiment proved that the proposed algorithm can also effectively improve the mining rate.
机译:自动,准确地提取数据包签名是大多数网络监控和取证应用程序流量识别的基础。 Apriori算法是完成任务的一种常用且有用的方法。对于大量Internet流量,传统的Apriori算法会产生大量的候选项目集,并且在扫描数据库时会占用大量的I / O成本。本文提出了一种改进方法。基于对候选人和公共签名数据库的修剪,它动态减少了扫描项目集的数量,从而提高了扫描效率。实验证明,该算法还可以有效提高挖掘速度。

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