Leveraging AI to Detect Insider Threats in Healthcare Organizations

Prof. Ranbir Singh

Abstract


This paper focuses on the use of AI to detect insider threats in healthcare systems, a growing concern with access to sensitive patient data. Machine learning models analyze user behavior and access patterns to identify anomalies that could signal malicious intent. By implementing natural language processing (NLP) for monitoring communication logs, the framework offers a multi-layered approach to threat detection. Testing on simulated hospital datasets demonstrates the framework's high accuracy in early threat identification, enhancing organizational security.

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