-
2
-
-
33646890686
-
Traffic classification on the fly
-
April
-
L. Bernaille, R. Teixeira, I. Akodkenou, A. Soule, and K. Salamatian. Traffic classification on the fly. SIGCOMM Comput. Commun. Rev., 36(2):23-26, April 2006.
-
(2006)
SIGCOMM Comput. Commun. Rev
, vol.36
, Issue.2
, pp. 23-26
-
-
Bernaille, L.1
Teixeira, R.2
Akodkenou, I.3
Soule, A.4
Salamatian, K.5
-
3
-
-
77953868170
-
Early application identification
-
New York, NY, USA, ACM
-
L. Bernaille, R. Teixeira, and K. Salamatian. Early application identification. In CoNEXT '06: Proceedings of the 2006 ACM CoNEXT conference, pages 1-12, New York, NY, USA, 2006. ACM.
-
(2006)
CoNEXT '06: Proceedings of the 2006 ACM CoNEXT conference
, pp. 1-12
-
-
Bernaille, L.1
Teixeira, R.2
Salamatian, K.3
-
6
-
-
48749130030
-
Traffic classification through simple statistical fingerprinting
-
M. Crotti, M. Dusi, F. Gringoli, and L. Salgarelli. Traffic classification through simple statistical fingerprinting. SIGCOMM Comput. Commun. Rev., 37(1):5-16, 2007.
-
(2007)
SIGCOMM Comput. Commun. Rev
, vol.37
, Issue.1
, pp. 5-16
-
-
Crotti, M.1
Dusi, M.2
Gringoli, F.3
Salgarelli, L.4
-
7
-
-
4944228528
-
A practical guide to support vector classification
-
Technical report, Taipei
-
C. W. Hsu, C. C. Chang, and C. J. Lin. A practical guide to support vector classification. Technical report, Taipei, 2003.
-
(2003)
-
-
Hsu, C.W.1
Chang, C.C.2
Lin, C.J.3
-
9
-
-
33847303101
-
Blinc: Multilevel traffic classification in the dark
-
T. Karagiannis, K. Papagiannaki, and M. Faloutsos. Blinc: multilevel traffic classification in the dark. SIGCOMM Comput. Commun. Rev., 35(4):229-240, 2005.
-
(2005)
SIGCOMM Comput. Commun. Rev
, vol.35
, Issue.4
, pp. 229-240
-
-
Karagiannis, T.1
Papagiannaki, K.2
Faloutsos, M.3
-
10
-
-
70350771144
-
Internet traffic classification demystified: Myths, caveats, and the best practices
-
H.-C. Kim, K. Claffy, M. Fomenkov, D. Barman, M. Faloutsos, and K. Lee. Internet traffic classification demystified: Myths, caveats, and the best practices. In ACM CoNEXT 2008.
-
ACM CoNEXT 2008
-
-
Kim, H.-C.1
Claffy, K.2
Fomenkov, M.3
Barman, D.4
Faloutsos, M.5
Lee, K.6
-
12
-
-
34249790654
-
Unexpected means of protocol inference
-
New York, NY, USA, ACM
-
J. Ma, K. Levchenko, C. Kreibich, S. Savage, and G. M. Voelker. Unexpected means of protocol inference. In IMC '06: Proceedings of the 6th ACM SIGCOMM conference on Internet measurement, pages 313-326, New York, NY, USA, 2006. ACM.
-
(2006)
IMC '06: Proceedings of the 6th ACM SIGCOMM conference on Internet measurement
, pp. 313-326
-
-
Ma, J.1
Levchenko, K.2
Kreibich, C.3
Savage, S.4
Voelker, G.M.5
-
13
-
-
35048887481
-
Flow clustering using machine learning techniques
-
A. Mcgregor, M. Hall, P. Lorier, and J. Brunskill. Flow clustering using machine learning techniques. In In PAM, pages 205-214, 2004.
-
(2004)
In PAM
, pp. 205-214
-
-
Mcgregor, A.1
Hall, M.2
Lorier, P.3
Brunskill, J.4
-
14
-
-
72049128163
-
-
A. Moore and K. Papagiannaki. Toward the Accurate Identification of Network Applications. In Proceedings of the Passive y Active Measurement Workshop (PAM2005), March/Apri 2005.
-
A. Moore and K. Papagiannaki. Toward the Accurate Identification of Network Applications. In Proceedings of the Passive y Active Measurement Workshop (PAM2005), March/Apri 2005.
-
-
-
-
15
-
-
33244467936
-
Internet traffic classification using bayesian analysis techniques
-
June
-
A. W. Moore and D. Zuev. Internet traffic classification using bayesian analysis techniques. SIGMETRICS Perform. Eval. Rev., 33(1):50-60, June 2005.
-
(2005)
SIGMETRICS Perform. Eval. Rev
, vol.33
, Issue.1
, pp. 50-60
-
-
Moore, A.W.1
Zuev, D.2
-
16
-
-
14944383480
-
Class-of-service mapping for qos: A statistical signature-based approach to ip traffic classification
-
M. Roughan, S. Sen, O. Spatscheck, and N. Duffield. Class-of-service mapping for qos: A statistical signature-based approach to ip traffic classification. In In IMCŠ04, pages 135-148, 2004.
-
(2004)
In IMCŠ04
, pp. 135-148
-
-
Roughan, M.1
Sen, S.2
Spatscheck, O.3
Duffield, N.4
-
17
-
-
19944406146
-
Accurate, scalable in-network identification of p2p traffic using application signatures
-
New York, NY, USA, ACM
-
S. Sen, O. Spatscheck, and D. Wang. Accurate, scalable in-network identification of p2p traffic using application signatures. In WWW '04: Proceedings of the 13th international conference on World Wide Web, pages 512-521, New York, NY, USA, 2004. ACM.
-
(2004)
WWW '04: Proceedings of the 13th international conference on World Wide Web
, pp. 512-521
-
-
Sen, S.1
Spatscheck, O.2
Wang, D.3
-
18
-
-
72049099462
-
A behavioral classification framework for p2p-tv applications
-
Technical Report WP3.1, TELECOM ParisTech (France, Politecnico di Torino Italy, January
-
S. Valenti, D. Rossi, M. Meo, M. Mellia, and P. Bermolen. A behavioral classification framework for p2p-tv applications. Technical Report WP3.1, TELECOM ParisTech (France), Politecnico di Torino (Italy), January 2009.
-
(2009)
-
-
Valenti, S.1
Rossi, D.2
Meo, M.3
Mellia, M.4
Bermolen, P.5
-
19
-
-
0003450542
-
-
Springer-Verlag New York, Inc, New York, NY, USA
-
V. N. Vapnik. The nature of statistical learning theory. Springer-Verlag New York, Inc., New York, NY, USA, 1995.
-
(1995)
The nature of statistical learning theory
-
-
Vapnik, V.N.1
-
20
-
-
72049097260
-
-
R. D. . A. M. Wei Li, Kaysar Abdin. Approaching real-time network traffic classification. Technical Report RR-06-12, Department of Computer Science, Queen Mary, University of London, Mile End Road, London E1 4NS, UK, October 2006.
-
R. D. . A. M. Wei Li, Kaysar Abdin. Approaching real-time network traffic classification. Technical Report RR-06-12, Department of Computer Science, Queen Mary, University of London, Mile End Road, London E1 4NS, UK, October 2006.
-
-
-
-
21
-
-
36249018389
-
-
Y. xiang Yang, R. Wang, Y. Liu, S. zhen Li, and X. yong Zhou. Solving p2p traffic identification problems via optimized support vector machines. In AICCSA [21], pages 165-171.
-
Y. xiang Yang, R. Wang, Y. Liu, S. zhen Li, and X. yong Zhou. Solving p2p traffic identification problems via optimized support vector machines. In AICCSA [21], pages 165-171.
-
-
-
|