实时正则表达式匹配与apache spark

Shaun R. Deaton, D. Brownfield, Leonard Kosta, Zhaozhong Zhu, Suzanne J. Matthews
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引用次数: 1

摘要

网络监控系统(NMS)是保护军队和企业网络的重要组成部分。随着政府和公司的增长,NMS收集的流量数据量也会成比例地增长。为了保护用户免受新出现的威胁,组织通常的做法是维护一系列自定义正则表达式(regex)模式,以便在NMS数据上运行。然而,网络流量的增长使得网络管理员越来越难以快速执行此过程。在本文中,我们描述了一种利用Apache Spark并行执行正则表达式匹配的新算法。我们在陆军工程研究与发展中心(ERDC)提供的3100万个Bro HTTP日志事件和569个正则表达式的数据集上测试了我们的方法。我们的结果表明,我们能够在1.047秒内处理1,250个事件,满足所需的实时定义。
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Real-time regex matching with apache spark
Network Monitoring Systems (NMS) are an important part of protecting Army and enterprise networks. As governments and corporations grow, the amount of traffic data collected by NMS grows proportionally. To protect users against emerging threats, it is common practice for organizations to maintain a series of custom regular expression (regex) patterns to run on NMS data. However, the growth of network traffic makes it increasingly difficult for network administrators to perform this process quickly. In this paper, we describe a novel algorithm that leverages Apache Spark to perform regex matching in parallel. We test our approach on a dataset of 31 million Bro HTTP log events and 569 regular expressions provided by the Army Engineer Research & Development Center (ERDC). Our results indicate that we are able to process 1, 250 events in 1.047 seconds, meeting the desired definition of real-time.
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