A Survey on Internet Traffic Identification

By A. Callado, Carlos Alberto Kamienski, G. Szabó, B. P. Gero, J. Kelner, S. Fernandes, D. Sadok. IEEE Communications Surveys and Tutorials, 2009

417 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Computer Networks and Communications, Hardware and Architecture

View Paper: https://www.semanticscholar.org/paper/220d623bd32fc5466a0191a10c93c01aef72869d

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Citations in the corpus

Network Anomaly Detection: Methods, Systems and Tools (2014, methodology): “Like [19], we also include a detailed discussion on flow and packet level capturing and preprocessing.”
Characterization of Encrypted and VPN Traffic using Time-related Features (2016, methodology): “The networking industry as well as the research community have dedicated many efforts to the research of these technologies and came up with several classification techniques (Callado et al., 2009).”
Characterization of Tor Traffic using Time based Features (2017, background): “The industry as well as the research community have dedicated many efforts to the study of these technologies, developing several classification techniques (Nguyen and Armitage, 2008; Callado et al., 2009).”
A Survey of Payload-Based Traffic Classification Approaches (2014, background): “On the other hand, the second mentioned survey [2], addresses the main techniques and problems associated with IP traffic classification.”
A survey of methods for encrypted traffic classification and analysis (2015, background): “Although there has been a lot of research on traffic classification in the past decade [25, 58, 71, 20, 32], most of the existing surveys do not explicitly consider research which targets encrypted traffic.”
Issues and future directions in traffic classification (2012, methodology): “Finally, approaches based on host communication patterns use heuristics that can effectively complement payload inspection techniques, especially for obfuscated traffic.”