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SF-TAP: Scalable and Flexible Traffic Analysis Platform Running on Commodity Hardware
Refereed Paper
Authors:
Yuuki Takano, Ryosuke Miura, and Shingo Yasuda, National Institute of Information and Communications Technology and Japan Advanced Institute of Science and Technology; Kunio Akashi, Japan Advanced Institute of Science and Technology; Tomoya Inoue, Japan Advanced Institute of Science and Technology and National Institute of Information and Communications Technology
Abstract:
Application-level network traffic analysis and sophisticated analysis techniques such as machine learning and stream data processing for network traffic require considerable computational resources. In addition, developing an application protocol analyzer is a tedious and time- consuming task. Therefore, we propose a scalable and flexible traffic analysis platform (SF-TAP) that provides an efficient and flexible application-level stream analysis of high-bandwidth network traffic. Our platform’s flexibility and modularity allow developers to easily implement multicore scalable application-level stream analyzers. Furthermore, SF-TAP is horizontally scalable and can therefore manage high-bandwidth network traffic. We achieve this scalability by separating network traffic based on traffic flows, forwarding the separated flows to multiple SF-TAP cells, each of which consists of a traffic capturer and application-level analyzers. In this study, we discuss the design and implementation of SF-TAP and provide details of its evaluation.
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BibTeX
@inproceedings {193176,
author = {Yuuki Takano and Ryosuke Miura and Shingo Yasuda and Kunio Akashi and Tomoya Inoue},
title = {{SF-TAP}: Scalable and Flexible Traffic Analysis Platform Running on Commodity Hardware},
booktitle = {29th Large Installation System Administration Conference (LISA15)},
year = {2015},
isbn = {978-1-931971-270},
address = {Washington, D.C.},
pages = {25--36},
url = {https://www.usenix.org/conference/lisa15/conference-program/presentation/takano},
publisher = {USENIX Association},
month = nov,
}
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