Fast, accurate, and lightweight real-time traffic identification method based on flow statistics

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4427 LNCS, Issue , 2007, Pages 255-259

  Tai, Masaki ^a   Ata, Shingo ^a   Oka, Ikuo ^a  

^a Osaka City University   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

DATA FLOW ANALYSIS; ONLINE SYSTEMS; PACKET NETWORKS; REAL TIME SYSTEMS; STATISTICAL METHODS; TRANSMISSION CONTROL PROTOCOL;

FLOW STATISTICS; OVERLAY NETWORKS; PROTOCOL NUMBER; TRAFFIC IDENTIFICATION METHOD;

TELECOMMUNICATION TRAFFIC;

EID: 38049144170     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-71617-4_30     Document Type: Conference Paper

References (4)

1. Andrew W. Moore and Konstantina Papagiannaki, "Toward the Accurate Identification of Network Applications," in Proceedings of PAM Passive and Active Network Measurement, pp. 41-54, March 2005.
2. Subhabrata Sen, Oliver Spatscheck, and Dongmei Wang, "Accurate, Scalable InNetwork Identification of P2P Traffic Using Application Signatures," in Proceedings of the 13th international conference on World Wide Web, pp. 512-521, May 2004.
3. Thomas Karagiannis, Konstantina Papagiannaki, and Michalis Faloutsos, "BLINC: Multilevel Traffic Classification in the Dark," in Proceedings of SIGCOMM Special Interest Group on Data Communication, pp. 229-240, August 2005.
4. Andrew W. Moore and Denis Zuev, "Internet Traffic Classification Using Bayesian Analysis Techniques," in Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems, pp. 50-60, June 2005.