A Practical Application of a Dataset Analysis in an Intrusion Detection System

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  • Additional Information
    • Publication Information:
      IEEE
    • Publication Date:
      2018
    • Abstract:
      In this paper a systematic analysis of a public intrusion detection dataset has been developed in order to understand how the traffic behaves in this particular context. This analysis is used for avoiding common pitfalls introduced because of a misunderstanding of data peculiarities and for selecting and tailoring correctly the algorithms. Specifically, we have employed machine learning algorithms to classify the traffic into normal and attack flows. In addition, it is important to decide what features should be evaluated. Typically, standard metrics do not take into account time spent in the classification, what is essential in an intrusion detection system. This is the reason why we introduce a metric that considers both the accuracy and the delay to make the decision and that is employed for evaluating machine learning algorithms in other domains. The conclusions obtained from our dataset analysis can be used to develop new models that could fit the data better than existing approaches.
    • Contents Note:
      Conference Acronym: NCA
    • Author Affiliations:
      University of A Coruna, A Coruna, CITIC Campus de Elvina, s/n 15071, Spain
    • ISBN:
      978-1-5386-7659-2
      978-1-5386-7658-5
    • Relation:
      2018 IEEE 17th International Symposium on Network Computing and Applications (NCA)
    • Accession Number:
      10.1109/NCA.2018.8548316
    • Rights:
      Copyright 2018, IEEE
    • AMSID:
      8548316
    • Conference Acronym:
      NCA
    • Date of Current Version:
      2018
    • Document Subtype:
      IEEE Conference
    • Notes:
      Conference Location: Cambridge, MA, USA, USA

      Conference Start Date: 1 Nov. 2018

      Conference End Date: 3 Nov. 2018
    • Accession Number:
      edseee.8548316
  • Citations
    • ABNT:
      FERNANDEZ, D. et al. A Practical Application of a Dataset Analysis in an Intrusion Detection System. 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Network Computing and Applications (NCA), 2018 IEEE 17th International Symposium on, [s. l.], p. 1–5, 2018. DOI 10.1109/NCA.2018.8548316. Disponível em: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.8548316. Acesso em: 13 ago. 2020.
    • AMA:
      Fernandez D, Vigoya L, Cacheda F, Novoa FJ, Lopez-Vizcaino MF, Carneiro V. A Practical Application of a Dataset Analysis in an Intrusion Detection System. 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Network Computing and Applications (NCA), 2018 IEEE 17th International Symposium on. November 2018:1-5. doi:10.1109/NCA.2018.8548316
    • APA:
      Fernandez, D., Vigoya, L., Cacheda, F., Novoa, F. J., Lopez-Vizcaino, M. F., & Carneiro, V. (2018). A Practical Application of a Dataset Analysis in an Intrusion Detection System. 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Network Computing and Applications (NCA), 2018 IEEE 17th International Symposium On, 1–5. https://doi.org/10.1109/NCA.2018.8548316
    • Chicago/Turabian: Author-Date:
      Fernandez, Diego, Laura Vigoya, Fidel Cacheda, Francisco J. Novoa, Manuel F. Lopez-Vizcaino, and Victor Carneiro. 2018. “A Practical Application of a Dataset Analysis in an Intrusion Detection System.” 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Network Computing and Applications (NCA), 2018 IEEE 17th International Symposium On, November, 1–5. doi:10.1109/NCA.2018.8548316.
    • Harvard:
      Fernandez, D. et al. (2018) ‘A Practical Application of a Dataset Analysis in an Intrusion Detection System’, 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Network Computing and Applications (NCA), 2018 IEEE 17th International Symposium on, pp. 1–5. doi: 10.1109/NCA.2018.8548316.
    • Harvard: Australian:
      Fernandez, D, Vigoya, L, Cacheda, F, Novoa, FJ, Lopez-Vizcaino, MF & Carneiro, V 2018, ‘A Practical Application of a Dataset Analysis in an Intrusion Detection System’, 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Network Computing and Applications (NCA), 2018 IEEE 17th International Symposium on, pp. 1–5, viewed 13 August 2020, .
    • MLA:
      Fernandez, Diego, et al. “A Practical Application of a Dataset Analysis in an Intrusion Detection System.” 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Network Computing and Applications (NCA), 2018 IEEE 17th International Symposium On, Nov. 2018, pp. 1–5. EBSCOhost, doi:10.1109/NCA.2018.8548316.
    • Chicago/Turabian: Humanities:
      Fernandez, Diego, Laura Vigoya, Fidel Cacheda, Francisco J. Novoa, Manuel F. Lopez-Vizcaino, and Victor Carneiro. “A Practical Application of a Dataset Analysis in an Intrusion Detection System.” 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Network Computing and Applications (NCA), 2018 IEEE 17th International Symposium On, November 1, 2018, 1–5. doi:10.1109/NCA.2018.8548316.
    • Vancouver/ICMJE:
      Fernandez D, Vigoya L, Cacheda F, Novoa FJ, Lopez-Vizcaino MF, Carneiro V. A Practical Application of a Dataset Analysis in an Intrusion Detection System. 2018 IEEE 17th International Symposium on Network Computing and Applications (NCA), Network Computing and Applications (NCA), 2018 IEEE 17th International Symposium on [Internet]. 2018 Nov 1 [cited 2020 Aug 13];1–5. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=edseee&AN=edseee.8548316