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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM66898
Volume:
10 |
8 |
Aug 2026
Pages:
1-8
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
COMPUTER SCIENCE
QUAID-E-MILLATH GOVERNMENT COLLEGE FOR WOMEN
COMPUTER SCIENCE
QUAID-E-MILLATH GOVERNMENT COLLEGE FOR WOMEN
Insider threat detection in healthcare EHR systems is challenging due to diverse user roles and complex access workflows. Conventional anomaly detection approaches often treat all users uniformly, resulting in high false alarm rates when legitimate role-specific behavior is misclassified as suspicious. This paper presents a role-aware anomaly detection approach for insider threat identification in healthcare environments. User activity logs are enriched with role-based contextual features that model expected access behavior for different healthcare roles, such as physicians, nurses, and administrative staff. Anomaly detection models are applied to identify deviations from role-consistent behavior patterns. Experimental evaluation using benchmark and simulated healthcare log data demonstrates that incorporating role awareness improves detection accuracy and significantly reduces false positives compared to role-agnostic approaches. The results highlight the importance of role context in developing reliable and practical insider threat detection systems for healthcare EHR environments.
KEYWORDS
Overall, the results confirm that role-aware anomaly detection provides a practical and effective improvement over role-agnostic approaches for insider threat detection in healthcare EHR systems. The proposed method enhances detection reliability while maintaining a lightweight and scalable implementation, making it suitable for real-world healthcare deployment.
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Publication Date
8/22/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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