AI based Pentest For EHR and Other Health Monitoring Devices

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.

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Publication Details

Published
2024-09-18
DOI
https://doi.org/10.1109/icosec61587.2024.10722070
Citations
6
Primary Topic
Context-Aware Activity Recognition Systems
Type
article
Field-Weighted Citation Impact
1.50
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article

AI based Pentest For EHR and Other Health Monitoring Devices

U Kumaran, M Gurupriya, Hitesh Surya Chinta, Akshita Uma Sai Maganti
6 citations
Context-Aware Activity Recognition Systems
1.50
article

AI based Pentest For EHR and Other Health Monitoring Devices

U Kumaran, M Gurupriya, Hitesh Surya Chinta, Akshita Uma Sai Maganti
article en
6 citations

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.

Amrita Vishwa Vidyapeetham (IN)
Openalex Percentile: Top 16%
Context-Aware Activity Recognition Systems
1.50
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