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Volumn , Issue , 2012, Pages

Challenges in network application identification

Author keywords

[No Author keywords available]

Indexed keywords

BOTNET; COMPUTER VIRUSES; FACINGS;

EID: 85084096364     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (32)

References (23)
  • 1
    • 85075113333 scopus 로고    scopus 로고
    • Bittorrent. http://www.bittorrent.com/.
  • 2
    • 85075111834 scopus 로고    scopus 로고
    • Flurry report. http://techcrunch.com/2012/01/09/flurry-mobile-appusage-up-to-94-minutes-per-day/.
    • Flurry Report
  • 4
    • 85075112468 scopus 로고    scopus 로고
    • Zynga. http://company.zynga.com/.
  • 8
    • 84893143817 scopus 로고    scopus 로고
    • Discoverer: Automatic protocol reverse engineering from network traces
    • W. Cui, J. Kannan, and H. J. Wang. Discoverer: Automatic Protocol Reverse Engineering from Network Traces. In 16th USENIX Security Symposium, 2007.
    • (2007) 16th USENIX Security Symposium
    • Cui, W.1    Kannan, J.2    Wang, H.J.3
  • 9
    • 85075098481 scopus 로고    scopus 로고
    • Offline/realtime traffic classification using semi-supervised learning
    • October
    • J. Erman, M. Arlitt, and C. Williamson. Offline/Realtime Traffic Classification Using Semi-Supervised Learning. In IFIP Performance, October 2007.
    • (2007) IFIP Performance
    • Erman, J.1    Arlitt, M.2    Williamson, C.3
  • 14
    • 38549084831 scopus 로고    scopus 로고
    • Accurate classification of the internet traffic based on the SVM method
    • June
    • Z. Li, R. Yuan, and X. Guan. Accurate Classification of the Internet Traffic Based on the SVM Method. In ICC, June 2007.
    • (2007) ICC
    • Li, Z.1    Yuan, R.2    Guan, X.3
  • 17
    • 84869166587 scopus 로고    scopus 로고
    • Internet traffic classification using bayesian analysis techniques
    • June
    • A. Moore and D. Zuev. Internet traffic classification using bayesian analysis techniques. In ACM Sigmetrics, June 2005.
    • (2005) ACM Sigmetrics
    • Moore, A.1    Zuev, D.2
  • 18
    • 14944383480 scopus 로고    scopus 로고
    • Class-of-service mapping for qos: A statistical signature-based approach to IP traffic classification
    • October
    • 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 ACM Internet Measurement Conference (IMC), October 2004.
    • (2004) ACM Internet Measurement Conference (IMC)
    • Roughan, M.1    Sen, S.2    Spatscheck, O.3    Duffield, N.4
  • 19
    • 19944406146 scopus 로고    scopus 로고
    • Accurate, scalable in-network identification of P2P traffic using application signatures
    • May
    • S. Sen, O. Spatscheck, and D. Wang. Accurate, Scalable In-Network Identification of P2P Traffic Using Application Signatures. In WWW2004, May 2004.
    • (2004) WWW2004
    • Sen, S.1    Spatscheck, O.2    Wang, D.3
  • 21
    • 33750283653 scopus 로고    scopus 로고
    • A preliminary performance comparison of five machine learning algorithms for practical IP traffic flow classification
    • October
    • N. Williams, S. Zander, and G. Armitage. A preliminary performance comparison of five machine learning algorithms for practical ip traffic flow classification. In ACM Sigcomm CCR, October 2006.
    • (2006) ACM Sigcomm CCR
    • Williams, N.1    Zander, S.2    Armitage, G.3
  • 23
    • 65249118724 scopus 로고    scopus 로고
    • Automated traffic classification and application identification using machine learning
    • November
    • S. Zander, T. Nguyen, and G. Armitage. Automated traffic classification and application identification using machine learning. In IEEE LCN, November 2005.
    • (2005) IEEE LCN
    • Zander, S.1    Nguyen, T.2    Armitage, G.3


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.