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Volumn , Issue , 2010, Pages

Profiling-by-association: A resilient traffic profiling solution for the Internet backbone

Author keywords

[No Author keywords available]

Indexed keywords

BACK-BONE NETWORK; DATA SETS; FLOW LEVEL; HARD PROBLEMS; INTERNET BACKBONE; INTERNET TRAFFIC; IP COMMUNICATIONS; RUNTIMES; TRAFFIC PROFILING;

EID: 79951601753     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1921168.1921171     Document Type: Conference Paper
Times cited : (23)

References (21)
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  • 6
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    • Using GMM and SVM-based techniques for the classification of SSH-Encrypted traffic
    • M. Dusi, A. Este, F. Gringoli, and L. Salgarelli. Using GMM and SVM-based techniques for the classification of SSH-Encrypted traffic. In IEEE ICC, 2009.
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    • Dusi, M.1    Este, A.2    Gringoli, F.3    Salgarelli, L.4
  • 7
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    • Identifying and Discriminating BetweenWeb and Peer-to-peer Traffic in the Network Core
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    • WWW, 2007
    • Erman, J.1    Mahanti, A.2    Arlitt, M.3    Williamson, C.4
  • 9
    • 79951610443 scopus 로고    scopus 로고
    • Applying latent Dirichlet allocation to group discovery in large graphs
    • K. Henderson and T. Eliassi-Rad. Applying latent Dirichlet allocation to group discovery in large graphs. In ACM SAC, 2009.
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    • Unveiling Core Network-Wide Communication Patterns through Application Traffic Activity Graph Decomposition
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    • ACM SIGMETRICS, 2009
    • Jin, Y.1    Esam, S.2    Zhang, Z.L.3
  • 14
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    • Mining communities in networks: A solution for consistency and its evaluation
    • H. Kwak, Y. Choi, Y.-H. Eom, H. Jeong, and S. Moon. Mining communities in networks: a solution for consistency and its evaluation. In IMC. ACM, 2009.
    • IMC ACM, 2009
    • Kwak, H.1    Choi, Y.2    Eom, Y.-H.3    Jeong, H.4    Moon, S.5
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    • Toward the accurate identification of network applications
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    • Internet Traffic Classification Using Bayesian Analysis Techniques
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    • Accurate, scalable in-network identification of p2p traffic using application signatures
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  • 21
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    • Profiling Internet Backbone Traffic: Behavior Models and Applications
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* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.