The rapid growth of telemedicine, cloud-assisted diagnostics, and picture archiving systems has made the secure handling of medical images a central requirement in modern healthcare. Yet many existing medical image ciphers are either computationally heavy, which often require complex arithmetic, multiple chaotic maps, or public-key primitives that hinder implementation on resource-constrained platforms and complicate formal security tuning. To address these limitations, we designed two lightweight, fully reversible image encryption schemes that achieve near-ideal statistical security while remaining practical for end-to-end clinical workflows. We designed two complementary symmetric ciphers that act directly in the pixel domain. The first is a spatial pixel-wise rotation and XOR-based lightweight encryption scheme (SPiRAL), that links pixels through chained XOR operations along image rows and columns, combined with index-dependent circular rotations and a lightweight key-driven permutation masking layer. The second is a chaotic reordering and nonlinear XOR encryption (CHRONEX), which employs coupled logistic maps to generate a key-dependent permutation of pixel indices followed by nonlinear S-box-based XOR diffusion. The experiments show that SPiRAL and CHRONEX produce cipher images with entropy values above 7.999 bits, number of pixels change rate (NPCR) and unified average changing intensity (UACI) with maximum of Formula: see text and Formula: see text respectively, and almost zero neighbour correlation, while guaranteeing exact recovery of the original images. Statistical significance testing confirms that the chaos-enhanced CHRONEX scheme, in particular, offers consistently higher randomness and differential robustness than competing techniques. These results demonstrate that carefully structured pixel-domain primitives can deliver transaction level security for medical images without sacrificing reversibility or real-time feasibility, making the proposed ciphers suitable for deployment from edge devices to hospital-scale archives.
Sundeep et al. (Sat,) studied this question.