Machine Learning and Big Data for Security Incident Response

Roberto Andrade, María Cazares, Iván Ortiz-Garces, Gustavo Navas

2022

Abstract

Cybersecurity attacks have grown exponentially. At present, cyberattacks have different attack vectors and techniques, generating a high impact on social and commercial worldwide. On the other hand, cybersecurity analysts need to process large amounts of data to detect patterns to make possible proactive security defences strategies. Incident response processes are based on detection tasks developed by a security analyst in the first stages of incident response. This work analyses the cognitive functions performed by cybersecurity analysts in the detection phase and combines big data and machine learning to enhance the detection processes of cyberattacks.

Paper Citation

in Harvard Style

Andrade R., Cazares M., Ortiz-Garces I. and Navas G. (2022). Machine Learning and Big Data for Security Incident Response. In Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC; ISBN 978-989-758-622-4, SciTePress, pages 739-744. DOI: 10.5220/0012045700003612

in Bibtex Style

@conference{isaic22,
author={Roberto Andrade and María Cazares and Iván Ortiz-Garces and Gustavo Navas},
title={Machine Learning and Big Data for Security Incident Response},
booktitle={Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC},
year={2022},
pages={739-744},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012045700003612},
isbn={978-989-758-622-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Symposium on Automation, Information and Computing - Volume 1: ISAIC
TI - Machine Learning and Big Data for Security Incident Response
SN - 978-989-758-622-4
AU - Andrade R.
AU - Cazares M.
AU - Ortiz-Garces I.
AU - Navas G.
PY - 2022
SP - 739
EP - 744
DO - 10.5220/0012045700003612
PB - SciTePress