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

doi:10.1007/978-3-030-55307-4_27

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

Artificial Intelligence and Facial Recognition Research Group (GIIAR)

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Original language	English
Title of host publication	Human Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies
Subtitle of host publication	Future Applications, IHIET 2020
Editors	Tareq Ahram, Redha Taiar, Karine Langlois, Arnaud Choplin
Publisher	Springer
Pages	173-179
Number of pages	7
ISBN (Print)	9783030553067
DOIs	https://doi.org/10.1007/978-3-030-55307-4_27
State	Published - 2021
Event	3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020 - Paris, France Duration: 27 Aug 2020 → 29 Aug 2020

Publication series

Name	Advances in Intelligent Systems and Computing
Volume	1253 AISC
ISSN (Print)	2194-5357
ISSN (Electronic)	2194-5365

Conference

Conference	3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020
Country	France
City	Paris
Period	27/08/20 → 29/08/20

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

Access to Document

10.1007/978-3-030-55307-4_27

Link to publication in Scopus

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Cite this

Martinez, M. A. Q., Leon Rugel, D. T., Espinoza Alcivar, C. J., & Vazquez, M. Y. L. (2021). A framework for selecting classification models in the intruder detection system using topsis. In T. Ahram, R. Taiar, K. Langlois, & A. Choplin (Eds.), Human Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020 (pp. 173-179). (Advances in Intelligent Systems and Computing; Vol. 1253 AISC). Springer. https://doi.org/10.1007/978-3-030-55307-4_27

Martinez, Miguel Angel Quiroz ; Leon Rugel, Deivid Temistocles ; Espinoza Alcivar, Carlos Jose ; Vazquez, Maikel Yelandi Leyva. / A framework for selecting classification models in the intruder detection system using topsis. Human Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020. editor / Tareq Ahram ; Redha Taiar ; Karine Langlois ; Arnaud Choplin. Springer, 2021. pp. 173-179 (Advances in Intelligent Systems and Computing).

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title = "A framework for selecting classification models in the intruder detection system using topsis",

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author = "Martinez, {Miguel Angel Quiroz} and {Leon Rugel}, {Deivid Temistocles} and {Espinoza Alcivar}, {Carlos Jose} and Vazquez, {Maikel Yelandi Leyva}",

note = "Funding Information: Acknowledgments. This work has been supported by the GIIAR research group and the Salesian Polytechnic University of Guayaquil. Publisher Copyright: {\textcopyright} 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.; null ; Conference date: 27-08-2020 Through 29-08-2020",

year = "2021",

doi = "10.1007/978-3-030-55307-4_27",

language = "English",

isbn = "9783030553067",

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publisher = "Springer",

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Martinez, MAQ, Leon Rugel, DT, Espinoza Alcivar, CJ & Vazquez, MYL 2021, A framework for selecting classification models in the intruder detection system using topsis. in T Ahram, R Taiar, K Langlois & A Choplin (eds), Human Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020. Advances in Intelligent Systems and Computing, vol. 1253 AISC, Springer, pp. 173-179, 3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020, Paris, France, 27/08/20. https://doi.org/10.1007/978-3-030-55307-4_27

A framework for selecting classification models in the intruder detection system using topsis. / Martinez, Miguel Angel Quiroz; Leon Rugel, Deivid Temistocles ; Espinoza Alcivar, Carlos Jose ; Vazquez, Maikel Yelandi Leyva.

Human Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020. ed. / Tareq Ahram; Redha Taiar; Karine Langlois; Arnaud Choplin. Springer, 2021. p. 173-179 (Advances in Intelligent Systems and Computing; Vol. 1253 AISC).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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T1 - A framework for selecting classification models in the intruder detection system using topsis

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AU - Leon Rugel, Deivid Temistocles

AU - Espinoza Alcivar, Carlos Jose

AU - Vazquez, Maikel Yelandi Leyva

N1 - 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.

PY - 2021

Y1 - 2021

KW - Intrusion Detection System (IDS)

KW - Machine learning

KW - NSL-KDD

KW - TOPSIS

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U2 - 10.1007/978-3-030-55307-4_27

DO - 10.1007/978-3-030-55307-4_27

M3 - Conference contribution

AN - SCOPUS:85089628131

SN - 9783030553067

T3 - Advances in Intelligent Systems and Computing

SP - 173

EP - 179

BT - Human Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies

A2 - Ahram, Tareq

A2 - Taiar, Redha

A2 - Langlois, Karine

A2 - Choplin, Arnaud

PB - Springer

Y2 - 27 August 2020 through 29 August 2020

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Martinez MAQ, Leon Rugel DT, Espinoza Alcivar CJ, Vazquez MYL. A framework for selecting classification models in the intruder detection system using topsis. In Ahram T, Taiar R, Langlois K, Choplin A, editors, Human Interaction, Emerging Technologies and Future Applications III - Proceedings of the 3rd International Conference on Human Interaction and Emerging Technologies: Future Applications, IHIET 2020. Springer. 2021. p. 173-179. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-3-030-55307-4_27