Towards Automatic Critical Infrastructure Protection through Machine Learning

TitleTowards Automatic Critical Infrastructure Protection through Machine Learning
Publication TypeConference Paper
Year of Publication2013
AuthorsL. Cazorla, C. Alcaraz, and J. Lopez
Conference Name8th International Conference on Critical Information Infrastructures Security
Volume8328
Pagination197-203
PublisherSpringer
Conference LocationAmsterdam, The Netherlands
ISSN Number0302-9743
Abstract

Critical Infrastructure Protection (CIP) faces increasing challenges in number and in sophistication, which makes vital to provide new forms of protection to face every day’s threats. In order to make such protection holistic, covering all the needs of the systems from the point of view of security, prevention aspects and situational awareness should be considered. Researchers and Institutions stress the need of providing intelligent and automatic solutions for protection, calling our attention to the need of providing Intrusion Detection Systems (IDS) with intelligent active reaction capabilities. In this paper, we support the need of automating the processes implicated in the IDS solutions of the critical infrastructures and theorize that the introduction of Machine Learning (ML) techniques in IDS will be helpful for implementing automatic adaptable solutions capable of adjusting to new situations and timely reacting in the face of threats and anomalies. To this end, we study the different levels of automation that the IDS can implement, and outline a methodology to endow critical scenarios with preventive automation. Finally, we analyze current solutions presented in the literature and contrast them against the proposed methodology

DOI10.1007%2F978-3-319-03964-0_18
Citation Key1805
Paper File: 
https://www.nics.uma.es/sites/default/files/papers/1805.pdf

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