Multiobjective classification with moGEP: an application in the network traffic domain

Created by W.Langdon from gp-bibliography.bib Revision:1.4340

  author =       "Marek Ostaszewski and Pascal Bouvry and 
                 Franciszek Seredynski",
  title =        "Multiobjective classification with moGEP: an
                 application in the network traffic domain",
  booktitle =    "GECCO '09: Proceedings of the 11th Annual conference
                 on Genetic and evolutionary computation",
  year =         "2009",
  editor =       "Guenther Raidl and Franz Rothlauf and 
                 Giovanni Squillero and Rolf Drechsler and Thomas Stuetzle and 
                 Mauro Birattari and Clare Bates Congdon and 
                 Martin Middendorf and Christian Blum and Carlos Cotta and 
                 Peter Bosman and Joern Grahl and Joshua Knowles and 
                 David Corne and Hans-Georg Beyer and Ken Stanley and 
                 Julian F. Miller and Jano {van Hemert} and 
                 Tom Lenaerts and Marc Ebner and Jaume Bacardit and 
                 Michael O'Neill and Massimiliano {Di Penta} and Benjamin Doerr and 
                 Thomas Jansen and Riccardo Poli and Enrique Alba",
  pages =        "635--642",
  address =      "Montreal",
  publisher =    "ACM",
  publisher_address = "New York, NY, USA",
  month =        "8-12 " # jul,
  organisation = "SigEvo",
  keywords =     "genetic algorithms, genetic programming, Gene
                 Expression Programming",
  isbn13 =       "978-1-60558-325-9",
  bibsource =    "DBLP,",
  DOI =          "doi:10.1145/1569901.1569989",
  abstract =     "The paper proposes a multiobjective approach to the
                 problem of malicious network traffic classification,
                 with specificity and sensitivity criteria as objective
                 functions for the problem. The multiobjective version
                 of Gene Expression Programming (GEP) called moGEP is
                 proposed and applied to find proper classifiers in the
                 multiobjective search space. The purpose of the
                 classifiers is to discriminate information about the
                 network traffic obtained from Idiotypic Network-based
                 Intrusion Detection System (INIDS), transformed into
                 time series. The proposed approach is validated using
                 the network traffic simulator ns2. Classifiers of high
                 accuracy are obtained and their diversity offers
                 interesting possibilities to the domain of network
  notes =        "GECCO-2009 A joint meeting of the eighteenth
                 international conference on genetic algorithms
                 (ICGA-2009) and the fourteenth annual genetic
                 programming conference (GP-2009).

                 ACM Order Number 910092.",

Genetic Programming entries for Marek Ostaszewski Pascal Bouvry Franciszek Seredynski