The use of artificial intelligence for the detection of cyber threats in electronic health systems  (EHS)

Vesna Simikić
Faculty of Technical Sciences University of Kragujevac, Svetog Save 65, Čačak, Serbia
simikic.vesna.85@gmail.com
DOI:  10.46793/BISEC25.273S

ABSTRACT:  Digitization of health systems through the implementation of electronic health systems (EHS) has significantly improved the efficiency and availability of health services, but at the same time in-creased exposure to sophisticated cyber threats. The application of artificial intelligence (AI) and machine learning (ML) in this context enables advanced anomaly detection and identification of suspicious patterns of user behavior, thereby improving system security. The 2024 and 2025 studies show that models like Isolation Forest, SVM, and EHR-BERT achieve high accuracy in detecting insider threats and unauthorized access in EHS systems. However, the implementation of these technologies faces challenges, including limited access to quality data, false positive alarms, complex IT infrastructure and non-compliance with legislation. Ethical aspects such as transparency of decisions, protection of privacy and responsibility for AI decisions require spe-cial attention. Future developments should rely on hybrid models, distributed learning and ex-plainable AI, with standardization of integration into clinical practice. Together, these elements can contribute to a more secure, resilient and ethically responsible digital health infrastructure. AI thus becomes a key tool for strengthening cyber security in modern healthcare.

KEYWORDS: electronic health systems, artificial intelligence, cyber threat, health record

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IZVOR: Proceedings of the 16th International Conference on Business Information Security BISEC’2025