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Towards Large Scale Packet Capture and Network Flow Analysis on Hadoop

机译:在Hadoop上实现大规模数据包捕获和网络流分析

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Network traffic continues to grow yearly at a compounded rate. However, network traffic is still being analyzed on vertically scaled machines that do not scale as well as distributed computing platforms. Hadoop's horizontally scalable ecosystem provides a better environment for processing these network captures stored in packet capture (PCAP) files. This paper proposes a framework called hcap for analyzing PCAPs on Hadoop inspired by the Rseaux IP Europens' (RIPE's) existing hadoop-pcap library but built completely from the ground up. The hcap framework improves several aspects of the hadoop-pcap library, namely protocol, error, and log handling. Results show that, while other methods still outperform hcap, it not only performs better than hadoop-pcap by 15% in scan queries and 18% in join queries, but it's more tolerant to broken PCAP entries which reduces preprocessing time and data loss, while also speeding up the conversion process used in other methods by 85%.
机译:网络流量继续按复合率增长。但是,在不缩放的垂直缩放机器和分布式计算平台上仍在分析网络流量。 Hadoop的水平可扩展生态系统提供了更好的环境,用于处理存储在数据包捕获(PCAP)文件中的这些网络捕获。本文提出了一个名为HCAP的框架,用于分析Hadoop的PCAPS,由RSEAUX IP(成熟)现有Hadoop-PCAP库的启发,但完全从地上构建。 HCAP框架改进了Hadoop-PCAP库的几个方面,即协议,错误和日志处理。结果表明,虽然其他方法仍然优于HCAP,但它不仅比Hadoop-PCAP更好地在扫描查询中的15%,而且加入查询中的18%,但它更容易损坏降低预处理时间和数据丢失的损坏还加快了其他方法中使用的转换过程85%。

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