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

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución de conferenciarevisión exhaustiva

8 Citas (Scopus)

Resumen

As the network has expanded considerably, security mechanisms are a key issue in networks. Intrusive activities, such as unauthorized access and data manipulation, are increasing. Therefore, the role of the Network Intrusion Detection System (NIDS) in monitoring network traffic for activity and determining whether an intrusion has occurred is very important. The performance of an IDS depends on the selection of the classification model and training data, however, many classifiers generate similar results when measuring performance. The technique of order of preference for similarity to the ideal solution (TOPSIS) is used to select one or more alternatives based on the criteria. The main objective is to present some classification models used in a data set to select the best alternative according to the performance criteria using the TOPSIS method. The deductive method and selection research technique were applied to study the NSL-KDD.

Idioma originalInglés
Título de la publicación alojadaHuman Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies
Subtítulo de la publicación alojadaFuture Applications, IHIET 2020
EditoresTareq Ahram, Redha Taiar, Karine Langlois, Arnaud Choplin
EditorialSpringer
Páginas173-179
Número de páginas7
ISBN (versión impresa)9783030553067
DOI
EstadoPublicada - 2021
Evento3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020 - Paris, Francia
Duración: 27 ago. 202029 ago. 2020

Serie de la publicación

NombreAdvances in Intelligent Systems and Computing
Volumen1253 AISC
ISSN (versión impresa)2194-5357
ISSN (versión digital)2194-5365

Conferencia

Conferencia3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020
País/TerritorioFrancia
CiudadParis
Período27/08/2029/08/20

Nota bibliográfica

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.

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