A framework for selecting classification models in the intruder detection system using topsis

Miguel Angel Quiroz Martinez, Deivid Temistocles Leon Rugel, Carlos Jose Espinoza Alcivar, Maikel Yelandi Leyva Vazquez

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Original languageEnglish
Title of host publicationHuman Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies
Subtitle of host publicationFuture Applications, IHIET 2020
EditorsTareq Ahram, Redha Taiar, Karine Langlois, Arnaud Choplin
PublisherSpringer
Pages173-179
Number of pages7
ISBN (Print)9783030553067
DOIs
StatePublished - 2021
Event3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020 - Paris, France
Duration: 27 Aug 202029 Aug 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1253 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020
CountryFrance
CityParis
Period27/08/2029/08/20

Bibliographical note

Funding Information:
Acknowledgments. This work has been supported by the GIIAR research group and the Salesian Polytechnic University of Guayaquil.

Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.

Keywords

  • Intrusion Detection System (IDS)
  • Machine learning
  • NSL-KDD
  • TOPSIS

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