An efficient image scheme for IoMT using 4D memristive hyperchaotic map

The security of Internet of Medical Things (IoMT) is closely linked to patient safety, unauthorized access may result in grave consequences. This paper reports a privacy protection scheme in the IoMT. A 4D memristive map (4D-TLMM) combining trigonometric functions, Logistic map and memristor is first designed with Lyapnov exponent and chaotic range increasing with the parameters, and its high randomness of resulting chaotic sequence is verified using NIST and sample entropy. Furthermore, a digital hardware testbed is developed to demonstrate its feasibility for hardware implementation. Then we present and analyze the specific situation of IoMT, and an image encryption algorithm (TLMM-IEA) using novel reflection scrambling and split diffusion is developed accordingly, which effectively disrupts the pixel relationships and ensures that only correct key can access patient information. After conducting numerical simulations on medical datasets, it is determined that the proposed scheme achieves average NPCR and UACI values of 99.6086 \(\%\) $\%$ and 33.4644 \(\%\) $\%$ , and possesses comprehensive robustness. Additionally, the encryption of \(224\times 224\) $224\times 224$ image using it only takes 0.0306 s, demonstrating its exceptional reliability in protecting IoMT security.