Chaos in fractals on FPGA – privacy preservation for a secure IoT node

The advent of high-speed networks and the Internet of Things (IoT) has significantly enhanced image communication. In hospital environments, edge devices have been seamlessly integrated with medical scanning equipment to capture and transfer human body images for e-diagnosis, thereby revolutionizing telemedicine and facilitating swift medical services. However, the imperative to safeguard these medical images from potential adversaries and intruders is crucial. This research introduces an innovative image encryption scheme leveraging the physical structure of square tree fractals implemented on the Intel Cyclone IV E Field Programmable Gate Array (FPGA). The design incorporates four layers of operations, with two dedicated to confusion and the remaining two to diffusion, ensuring robust encryption. Circular left/right shifts and Linear Feedback Shift Register (LFSR)-generated pseudo-random sequences govern Confusion I and II, while Diffusion I and II are supported by the logistic map. The physical fractal structure, combined with the logistic map and LFSR, constitutes the key, resulting in an exceptionally high keyspace compared to prior works. The proposed scheme achieves a noteworthy entropy of 7.9968 and 7.9969 for Digital Imaging in Communications and Medicine (DICOM) and grayscale images, respectively. Additionally, it exhibits a near-zero correlation. Importantly, the design utilizes only 1