Security Incident Classification Applied to Automated Decisions Using Machine Learning

Eduardo Eloy Loza Pacheco; Mayra Lorena Díaz Sosa; Christian Carlos Delgado Elizondo; Miguel Jesús Torres Ruiz; Dulce Lourdes Loza Pacheco

doi:10.1007/978-3-030-89586-0_3

Security Incident Classification Applied to Automated Decisions Using Machine Learning

Eduardo Eloy Loza Pacheco, Mayra Lorena Díaz Sosa, Christian Carlos Delgado Elizondo, Miguel Jesús Torres Ruiz, Dulce Lourdes Loza Pacheco

Centro de Investigación en Computación (CIC)

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

Abstract

There is an immense number of attacks on the logical infrastructure of an organization. Cybersecurity professionals need tools to help discriminate levels of attacks to design operational plans to prevent, mitigate, and restore without significant damage to an organization’s resources. Machine learning helps build valuable models to identify relevant values of a vulnerability vector attack needed to improve our security plan. The following work presents a framework that uses a machine learning model that classifies the level of an incident detection indicator.

Original language	English
Title of host publication	Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings
Editors	Miguel Félix Mata-Rivera, Roberto Zagal-Flores
Publisher	Springer Science and Business Media Deutschland GmbH
Pages	23-34
Number of pages	12
ISBN (Print)	9783030895853
DOIs	https://doi.org/10.1007/978-3-030-89586-0_3
State	Published - 2021
Event	10th International Congress on Telematics and Computing, WITCOM 2021 - Virtual, Online Duration: 8 Nov 2021 → 12 Nov 2021

Publication series

Name	Communications in Computer and Information Science
Volume	1430 CCIS
ISSN (Print)	1865-0929
ISSN (Electronic)	1865-0937

Conference

Conference	10th International Congress on Telematics and Computing, WITCOM 2021
City	Virtual, Online
Period	8/11/21 → 12/11/21

Keywords

Cybersecurity
Machine learning
Preparation of security incidents

Access to Document

10.1007/978-3-030-89586-0_3

Cite this

Loza Pacheco, E. E., Díaz Sosa, M. L., Delgado Elizondo, C. C., Torres Ruiz, M. J., & Loza Pacheco, D. L. (2021). Security Incident Classification Applied to Automated Decisions Using Machine Learning. In M. F. Mata-Rivera, & R. Zagal-Flores (Eds.), Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings (pp. 23-34). (Communications in Computer and Information Science; Vol. 1430 CCIS). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-89586-0_3

Loza Pacheco, Eduardo Eloy ; Díaz Sosa, Mayra Lorena ; Delgado Elizondo, Christian Carlos et al. / Security Incident Classification Applied to Automated Decisions Using Machine Learning. Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings. editor / Miguel Félix Mata-Rivera ; Roberto Zagal-Flores. Springer Science and Business Media Deutschland GmbH, 2021. pp. 23-34 (Communications in Computer and Information Science).

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abstract = "There is an immense number of attacks on the logical infrastructure of an organization. Cybersecurity professionals need tools to help discriminate levels of attacks to design operational plans to prevent, mitigate, and restore without significant damage to an organization{\textquoteright}s resources. Machine learning helps build valuable models to identify relevant values of a vulnerability vector attack needed to improve our security plan. The following work presents a framework that uses a machine learning model that classifies the level of an incident detection indicator.",

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Loza Pacheco, EE, Díaz Sosa, ML, Delgado Elizondo, CC, Torres Ruiz, MJ & Loza Pacheco, DL 2021, Security Incident Classification Applied to Automated Decisions Using Machine Learning. in MF Mata-Rivera & R Zagal-Flores (eds), Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings. Communications in Computer and Information Science, vol. 1430 CCIS, Springer Science and Business Media Deutschland GmbH, pp. 23-34, 10th International Congress on Telematics and Computing, WITCOM 2021, Virtual, Online, 8/11/21. https://doi.org/10.1007/978-3-030-89586-0_3

Security Incident Classification Applied to Automated Decisions Using Machine Learning. / Loza Pacheco, Eduardo Eloy; Díaz Sosa, Mayra Lorena; Delgado Elizondo, Christian Carlos et al.
Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings. ed. / Miguel Félix Mata-Rivera; Roberto Zagal-Flores. Springer Science and Business Media Deutschland GmbH, 2021. p. 23-34 (Communications in Computer and Information Science; Vol. 1430 CCIS).

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

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AU - Loza Pacheco, Dulce Lourdes

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KW - Machine learning

KW - Preparation of security incidents

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Loza Pacheco EE, Díaz Sosa ML, Delgado Elizondo CC, Torres Ruiz MJ, Loza Pacheco DL. Security Incident Classification Applied to Automated Decisions Using Machine Learning. In Mata-Rivera MF, Zagal-Flores R, editors, Telematics and Computing - 10th International Congress, WITCOM 2021, Proceedings. Springer Science and Business Media Deutschland GmbH. 2021. p. 23-34. (Communications in Computer and Information Science). doi: 10.1007/978-3-030-89586-0_3

Security Incident Classification Applied to Automated Decisions Using Machine Learning

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