Graption: A graph-based P2P traffic classification framework for the internet backbone

Computer Networks

Volumn 55, Issue 8, 2011, Pages 1909-1920

  Iliofotou, Marios ^a   Kim, Hyun Chul ^b   Faloutsos, Michalis ^a   Mitzenmacher, Michael ^c   Pappu, Prashanth ^d   Varghese, George ^e  

^a UNIVERSITY OF CALIFORNIA   (United States)

^b Seoul National University   (South Korea)

^c HARVARD UNIVERSITY   (United States)

^d Conviva Inc ^*  (United States)

^e UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Behavioral approach; Graph mining; Peer to peer; Traffic classification

Indexed keywords

BEHAVIORAL-APPROACH; CLASSIFICATION FRAMEWORK; DISPERSION GRAPH; FLOW-LEVEL; GRAPH MINING; GRAPH-BASED; HOST-BASED; INTERNET APPLICATION; INTERNET BACKBONE; IP ADDRESSS; MONITORING NETWORK; NETWORK ADMINISTRATOR; NEW APPLICATIONS; PEER TO PEER; PROOF OF CONCEPT; TRAFFIC CLASSIFICATION;

DISTRIBUTED COMPUTER SYSTEMS; INTERNET; INTERNET PROTOCOLS; PEER TO PEER NETWORKS; TELECOMMUNICATION NETWORKS;

TELECOMMUNICATION TRAFFIC;

EID: 79955760469     PISSN: 13891286     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.comnet.2011.01.020     Document Type: Article

References (40)

1. E.G. Allan, W.H. Turkett, E.W. Fulp, Using network motifs to identify application protocols, in: IEEE GLOBECOM, 2009.
2. G. Barlett, J. Heidemann, C. Papadopoulos, Inherent behaviors of on-line detection of peer-to-peer file sharing, in: IEEE GI, 2007.
3. L. Bernaille, R. Teixeira, K. Salamatian, Early application identification, in: ACM CoNEXT, 2006.
4. D. Bonfiglio, M. Mellia, M. Meo, D. Rossi, P. Tofanelli, Revealing Skype Traffic: when randomness plays with you, in: ACM SIGCOMM, 2007.
5. CAIDA. http://www.caida.org.
6. M.P. Collins, M.K. Reiter, Hit-List worm detection and bot identification in large networks using protocol graphs, in: RAID, 2007.
7. F. Constantinou, P. Mavrommatis, Identifying known and unknown peer-to-peer traffic, in: IEEE NCA, 2006.
8. DatCat, Internet Measurement Data Catalog. http://www.datcat.org.
9. D. Ellis, J. Aiken, K. Attwood, S. Tenarglia, A behavioral approach to worm detection, in: ACM CCS WORM, 2004.
10. J. Erman, M. Arlitt, A. Mahanti, Traffic classification using clustering algorithms, in: ACM SIGCOMM MineNet, 2006.
11. A. Este, F. Gringoli, and L. Slagerelli On the stability of the information carried by traffic flow features at the packet level ACM SIGCOMM CCR 39 3 2009 13 18
12. P. Fogla, M. Sharif, R. Perdisci, O. Kolesnikov, W. Lee, Polymorphic blending attacks, in: USENIX Security Symposium, 2006.
13. A. Gerber, J. Houle, H. Nguyen, M. Roughan, S. Sen, P2P, the Gorilla in the cable, in: National Cable and Telecommunications Association (NCTA), 2003.
14. G. Gu, R. Perdisci, J. Zhang, W. Lee. BotMiner: clustering analysis of network traffic from protocol- and structure-independent botnet detection, in: USENIX Security Symposium, 2008.
15. P. Haffner, S. Sen, O. Spatscheck, D. Wang, ACAS: automated construction of application signatures, in: ACM SIGCOMM MineNet, 2005.
16. M. Iliofotou, M. Faloutsos, M. Mitzenmacher, Exploiting dynamicity in graph-based traffic analysis: techniques and applications, in: ACM CoNEXT, 2009.
17. M. Iliofotou, B. Gallagher, G. Xie, T. Eliassi-Rad, M. Faloutsos, Profiling-by-association: a resilient traffic profiling solution for the internet backbone, in: ACM CoNEXT, 2010.
18. M. Iliofotou, H. Kim, P. Pappu, M. Faloutsos, M. Mitzenmacher, G. Varghese, Graph-based P2P traffic classification at the internet backbone, in: IEEE GI, 2009.
19. M. Iliofotou, P. Pappu, M. Faloutsos, M. Mitzenmacher, S. Singh, G. Varghese, Network monitoring using traffic dispersion graphs (TDGs), in: ACM IMC, 2007.
20. IPOQUE - Bandwidth Management with Deep Packet Inspection, Internet Study: The Impact of P2P File Sharing, Voice over IP, Instant Messaging, One-Click Hosting and Media Streaming on the Internet, 2009.
21. Y. Jin, S. Esam, Z.L. Zhang, Unveiling core network-wide communication patterns through application traffic activity graph decomposition, in: ACM SIGMETRICS, 2009.
22. W. John, S. Tafvelin, Heuristics to classify internet backbone traffic based on connection patterns, in: IEEE ICOIN, 2008.
23. T. Karagiannis, A. Broido, N. Brownlee, K. Claffy, M. Faloutsos, Is P2P dying or just hiding? in: IEEE GLOBECOM, 2004.
24. T. Karagiannis, A. Broido, M. Faloutsos, K. claffy, Transport layer identification of P2P traffic, in: ACM IMC, 2004.
25. T. Karagiannis, K. Papagiannaki, M. Faloutsos, BLINC: multi-level traffic classification in the dark, in: ACM SIGCOMM, 2005.
26. H. Kim, K. Claffy, M. Fomenkov, D. Barman, M. Faloutsos, K. Lee, Internet traffic classification demystified: myths, caveats, and the best practices, in: ACM CoNEXT, 2008.
27. C. Labovitz, S. Lekel-johnson, J. Oberheide, F. Jahanian, Internet inter-domain traffic, in: ACM SIGCOMM, 2010.
28. J. Ma, K. Levchenko, C. Kreibich, S. Savage, G.M. Voelker, Unexpected means of protocol inference, in: ACM IMC, 2006.
29. A. McGregor, M. Hall, P. Lorier, J. Brunskill, Flow clustering using machine learning techniques, in: PAM, 2004.
30. A. Moore, K. Papagiannaki, Toward the accurate identification of network applications, in: PAM, 2005.
31. M.E.J. Newman The structure and function of complex networks SIAM Review 45 2003 167
32. T.T.T. Nguyen, G. Armitage, A survey of techniques for internet traffic classification using machine learning, IEEE Communications Surveys and Tutorials, 4th ed., March, 2008.
33. S. Sen, O. Spatscheck, D. Wang, Accurate, scalable in-network identification of p2p traffic using application signatures, in: WWW, 2004.
34. S. Sen, and J. Wang Analyzing peer-to-peer traffic across large networks IEEE/ACM Transaction on Networking 12 2 2004 219 232
35. G. Tan, M. Poletto, J. Guttag, F. Kaashoek, Role classification of hosts within enterprise networks based on connection patterns, in: USENIX Annual Technical Conference, 2003.
36. I. Trestian, S. Ranjan, A. Kuzmanovic, A. Nucci, Unconstrained endpoint profiling (Googling the Internet), in: ACM SIGCOMM, 2008.
37. G. Urvoy-Keller, T. En-Najjary, Challenging statistical classification for operational usage: the ADSL case, in: ACM IMC, 2009.
38. I.H. Witten, and E. Frank Data Mining: Practical Machine Learning Tools and Techniques 2nd ed. 2005 Morgan Kaufman
39. Y. Xie, V. Sekar, D. Maltz, M. Reiter, H. Zhan, Forensic analysis of epidemic attacks in federated networks, in: IEEE ICNP, 2006.
40. K. Xu, Z. Zhang, S. Bhattacharyya, Profiling internet backbone traffic: behavior models and applications, in: ACM SIGCOMM, 2005.