@inproceedings{0df3b494eeb34d8eaeb2d945b71e3881,
title = "Internet traffic analysis in a large university town: A graphical and clustering approach",
abstract = "Campus networks consist of a rich diversity of end hosts including wired desktops, servers, and wireless BYOD devices such as laptops and smartphones, which are often compromised in insecure networks. Making sense of traffic behaviors of end hosts in campus networks is a daunting task due to the open nature of the network, heterogeneous devices, high mobility of end users, and a wide range of applications. To address these challenges, this paper applies a combination of graphical approaches and spectral clustering to group the Internet traffic of campus networks into distinctive traffic clusters in a divide-and-conquer manner. Specifically, we first model the data communication between a particular subnet of campus networks and the Internet on a specific application port via bipartite graphs, and subsequently use the one-mode projection to capture behavior similarity of end hosts in the same subnet for the same network applications. Finally we apply a spectral clustering algorithm to explore the behavior similarity to identify distinctive application clusters within each subnet. Our experimental results have demonstrated the benefits of our proposed method for analyzing Internet traffic of a large university town to discover anomalous behaviors and to uncover distinctive temporal and spatial traffic patterns.",
keywords = "Bipartite graph, Campus network, Spectral clustering, Traffic analysis",
author = "Weitao Weng and Kai Lei and Kuai Xu and Xiaoyou Liu and Tao Sun",
note = "Funding Information: L. Kai—This work has been financially supported by Shenzhen General Research project No: JCYJ20150626111057728 and Key Research Project No: JCYJ20151014093505032, JSGG20140516162852628 and JCYJ20151030154330711. Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 17th International Conference on Web-Age Information Management, WAIM 2016 ; Conference date: 03-06-2016 Through 05-06-2016",
year = "2016",
doi = "10.1007/978-3-319-39937-9_29",
language = "English (US)",
isbn = "9783319399362",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "378--389",
editor = "Jianliang Xu and Nan Zhang and Dexi Liu and Bin Cui and Xiang Lian",
booktitle = "Web-Age Information Management - 17th International Conference, WAIM 2016, Proceedings",
}