著者

TAKANO Yuuki MIURA Ryosuke YASUDA Shingo AKASHI Kunio INOUE Tomoya

出版者

日本ソフトウェア科学会

雑誌

コンピュータ ソフトウェア (ISSN:02896540)

巻号頁・発行日

vol.36, no.3, pp.3_85-3_103, 2019-07-25 (Released:2019-08-24)

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Application-level network traffic analysis and sophisticated analysis techniques, such as machine learningand stream data processing for network traffic, require considerable computationalresources.In addition, developing an application protocol analyzer is a tediousand time-consuming task.Therefore, we propose a scalable and flexible traffic analysis platform (SF-TAP) for the efficientand flexible application-level streamanalysis of high-bandwidth network traffic.By using our flexible modular platform, developers can easilyimplement multicore scalable application-level stream analyzers.Furthermore, as SF-TAP is horizontally scalable, it manageshigh-bandwidth network traffic.To achieve this scalability, we separate the network trafficbased on traffic flows, and forward the separated flows to multipleSF-TAP cells, each comprising a traffic capturer andapplication-level analyzers.This study discusses the design, implementation and detailed evaluation of SF-TAP.