Publication

Abstract : The increasing reliance on Electronic Health Records (EHRs) and health monitoring devices has made healthcare systems vulnerable to cyberattacks. This research proposes an AI-based penetration testing framework to address these security concerns. By integrating machine learning techniques, our framework offers a more realistic approach to learning actual attack patterns, improving detection accuracy and response time compared to traditional methods. The framework’s ability to minimize false positives and adapt to new threats demonstrates its effectiveness in strengthening healthcare system security. This research highlights the potential of AI-driven penetration testing in safeguarding patient information and protecting the integrity of healthcare systems. By identifying and addressing vulnerabilities, this framework can contribute to a more secure and resilient healthcare environment.