Using Machine Learning to Detect Ransomware Attacks on Electronic Health Records (EHRs)

dc.contributor.advisorDuffany, Jeffrey
dc.contributor.authorDurán Zamora, Miguel
dc.date.accessioned2026-01-20T14:58:24Z
dc.date.issued2025
dc.descriptionDesign Project Article for the Graduate Programs at Polytechnic University of Puerto Rico
dc.description.abstractRansomware attacks have always been a burden for many industries, and nowadays, with the advancement of technology and computers, they have taken over everything. One crucial industry is the health industry, which has been a victim of these attacks for a while. Could we explore ways to detect and mitigate these attacks in critical areas, such as health? That’s why in this article, we will discuss how we can use machine learning to detect ransomware attacks on electronic health records. Key Terms ⎯ Detect, Electronic Health Records, Machine Learning, Ransomware.
dc.identifier.citationDurán Zamora, M. (2025). Using Machine Learning to Detect Ransomware Attacks on Electronic Health Records (EHRs) [Unpublished manuscript]. Graduate School, Polytechnic University of Puerto Rico.
dc.identifier.urihttps://hdl.handle.net/20.500.12475/3246
dc.language.isoen
dc.publisherPolytechnic University of Puerto Rico
dc.relation.haspartSan Juan
dc.relation.ispartofComputer Science Program
dc.relation.ispartofseriesFall-2025
dc.rights.holderPolytechnic University of Puerto Rico,Graduate School
dc.rights.licenseAll rights reserved
dc.subject.lcshPolytechnic University of Puerto Rico--Graduate students--Research
dc.subject.lcshPolytechnic University of Puerto Rico--Graduate students--Posters
dc.titleUsing Machine Learning to Detect Ransomware Attacks on Electronic Health Records (EHRs)
dc.typeArticle
dc.typePoster

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