Obfuscated AES cryptosystem for secure medical imaging systems in IoMT edge devices

Internet of Medical Things (IoMT) driven health is the most advantageous aspect of technology in the global healthcare industry. Incorporating personalized health data into the formal multimedia electronic health record has tremendous potential to enhance personalized healthcare. The transition from medical data paperwork to health records increases legibility, reduces the in-hospital congestion services, performs remote patient monitoring. Hence, the secure exchange of health records to the cloud is paramount. Many cryptography schemes provide peer-to-peer communication by ensuring health record confidentiality and integrity over public networks. This paper presents an effective and scalable Advanced Encryption Standard (AES) cryptosystem to ensure better resistance against well-acknowledged attacks and secure the health record, specifically medical imaging, successfully before transmission. The main contribution of this paper is to build a secure hardware-software co-design of a scalable and reconfigurable medical imaging processing system by integrating authentication-based approaches such as PUF and TRNG to the AES cryptosystem on ZedBoard with minimum possible overhead. Simulation and experimental results in terms of statistical tests, PUF evaluation metrics, authentication, and NIST analysis illustrate the efficacy of the proposed system. Furthermore, we have employed a threat model, analyzed several hardware attacks such as reverse engineering, side-channel attacks, differential attacks, key-sensitivity attacks, etc., and conducted an in-depth security evaluation to show the robustness and attack resiliency of our proposed medical imaging processing system.