Abstract
Designing and deploying highly secure and efficient encryption algorithms for Internet of Things (IoT) devices, particularly resource-constrained medical devices, poses a significant challenge. Chaotic systems, with their sensitivity to initial conditions and capacity to generate pseudorandom signals, offer a promising solution to address the limitations of image encryption in IoT devices. Based on a novel memristive multi-attractor Hénon map model (MMHM) that is able to generate hyperchaotic signals, this article proposes a lightweight image encryption scheme for medical Internet of Medical Things (IoMT) devices, effectively addressing numerous deficiencies in existing approaches. To overcome the leakage risks present in existing schemes during key distribution, the initial key is encrypted using an asymmetric encryption algorithm. A key update mechanism is also employed, guaranteeing that each encrypted image is assigned a unique key, which effectively nullifies the risk of differential attacks. Additionally, a geometric transformation-based disruption algorithm is introduced, achieving exceptionally high levels of chaos with minimal computational overhead while providing robust resistance to cropping attacks. Notably, the solution is deployed on a digital circuit platform based on the STM32 microcontroller. Experimental results demonstrate that this method significantly outperforms traditional approaches in resisting typical attacks. It effectively compensates for vulnerabilities in the key distribution and key update mechanisms of conventional schemes, substantially enhancing both cryptographic security and efficiency.