AI for Medical Image Security: A Comprehensive Review of Techniques and Challenges
Authors/Creators
- 1. Department of Electrical Systems Engineering, LIMOSE Laboratory, Faculty of Technology
Description
Ensuring the security of sensitive medical data, including patient records and medical images, is paramount in the healthcare sector due to the risks of unauthorized access and data breaches. As healthcare information is increasingly transmitted through unsecured channels, maintaining its confidentiality, integrity, and authenticity is essential. This review examines AI-driven security techniques such as encryption, anomaly detection, and privacy-preserving algorithms, which play a crucial role in protecting medical data. By enhancing regulatory compliance and fostering trust in digital healthcare systems, these methods contribute significantly to data security. Additionally, this paper explores recent advancements in AI-based medical image protection and highlights key challenges and future research directions in the field of medical data security.
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proceedings_A2I_2025-pages-3.pdf
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Related works
- Is published in
- Conference proceeding: 10.5281/zenodo.17542999 (DOI)