A taxonomy of malicious traffic for intrusion detection systems

Hanan Hindy, Elike Hodo, Ethan Bayne, Amar Seeam, Robert Atkinson, Xavier Bellekens

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

3 Citations (Scopus)
2 Downloads (Pure)

Abstract

With the increasing number of network threats it is essential to have a knowledge of existing and new network threats in order to design better intrusion detection systems. In this paper we propose a taxonomy for classifying network attacks in a consistent way, allowing security researchers to focus their efforts on creating accurate intrusion detection systems and targeted datasets.

Original languageEnglish
Title of host publication2018 International Conference on Cyber Situational Awareness, Data Analytics and Assessment, CyberSA 2018
Place of PublicationPiscataway, N.J.
Number of pages4
ISBN (Electronic)9781538645659
DOIs
Publication statusPublished - 28 Nov 2018
Event2018 International Conference on Cyber Situational Awareness, Data Analytics and Assessment, CyberSA 2018 - Glasgow, United Kingdom
Duration: 11 Jun 201812 Jun 2018

Conference

Conference2018 International Conference on Cyber Situational Awareness, Data Analytics and Assessment, CyberSA 2018
CountryUnited Kingdom
CityGlasgow
Period11/06/1812/06/18

Keywords

  • network threats
  • detection system
  • network attacks

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  • Cite this

    Hindy, H., Hodo, E., Bayne, E., Seeam, A., Atkinson, R., & Bellekens, X. (2018). A taxonomy of malicious traffic for intrusion detection systems. In 2018 International Conference on Cyber Situational Awareness, Data Analytics and Assessment, CyberSA 2018 [8551386]. https://doi.org/10.1109/CyberSA.2018.8551386