An investigation on the identification of VoIP traffic: Case study on Gtalk and Skype

Created by W.Langdon from gp-bibliography.bib Revision:1.3973

@InProceedings{Alshammari:2010:CNSM,
  author =       "Riyad Alshammari and A. Nur Zincir-Heywood",
  title =        "An investigation on the identification of {VoIP}
                 traffic: Case study on Gtalk and Skype",
  booktitle =    "2010 International Conference on Network and Service
                 Management (CNSM)",
  year =         "2010",
  month =        "25-29 " # oct,
  pages =        "310--313",
  abstract =     "The classification of encrypted traffic on the fly
                 from network traces represents a particularly
                 challenging application domain. Recent advances in
                 machine learning provide the opportunity to decompose
                 the original problem into a subset of classifiers with
                 non-overlapping behaviours, in effect providing further
                 insight into the problem domain. Thus, the objective of
                 this work is to classify VoIP encrypted traffic, where
                 Gtalk and Skype applications are taken as good
                 representatives. To this end, three different machine
                 learning based approaches, namely, C4.5, AdaBoost and
                 Genetic Programming (GP), are evaluated under data sets
                 common and independent from the training condition. In
                 this case, flow based features are employed without
                 using the IP addresses, source/destination ports and
                 payload information. Results indicate that C4.5 based
                 machine learning approach has the best performance.",
  keywords =     "genetic algorithms, genetic programming, AdaBoost,
                 C4.5, Gtalk, IP address, Skype, VoIP encrypted traffic,
                 machine learning, source/destination port, Internet
                 telephony, learning (artificial intelligence),
                 telecommunication traffic",
  DOI =          "doi:10.1109/CNSM.2010.5691210",
  notes =        "Also known as \cite{5691210}",
}

Genetic Programming entries for Riyad Alshammari Nur Zincir-Heywood

Citations