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Revista Cubana de Informática Médica

On-line version ISSN 1684-1859

Abstract

PERDIGON LLANES, Rudibel  and  ORELLANA GARCIA, Arturo. Intrusion-Detection Systems for Healthcare Institutions’ Data Networks. RCIM [online]. 2021, vol.13, n.2  Epub Dec 01, 2021. ISSN 1684-1859.

The use of digital technologies in medical institutions allows to improve the quality of health services. However, its use increases the vulnerabilities and security risks of these organizations. Currently, digital systems in the health sector represent an attractive target for cyber-criminals because they constitute poorly protected sources of valuable information. The study of the literature made it possible to identify a lack of research aimed at increasing security in health institutions data networks. The objective of this research is to carry out a literature review on the main open source Intrusion Detection Systems currently existing to strengthen security in the data networks of these organizations. The superiority of Snort and Suricata as open source tools for intrusion detection in data networks was identified.

Keywords : IDS; computer security; computer systems; computer communication networks.

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