Enhancing Medical Image Privacy in IoT with Bit-Plane Level Encryption using Chaotic Map

Fatima Asiri¹Wajdan Al Malwi¹Tamara Zhukabayeva²Ibtehal Nafea³Abdullah Aziz^4*Nadhmi A. Gazem³Abdullah Qayyum⁵

• ¹King Khalid University, Abha, Saudi Arabia
• ²L.N. Gumilyov Eurasian National University, Nur-sultan, Kazakhstan
• ³Taibah University, Medina, Al Madinah, Saudi Arabia
• ⁴Umeå University, Umeå, Västerbotten, Sweden
• ⁵University of Sussex, Brighton, United Kingdom

Preserving privacy is a critical concern in medical imaging, especially in resource-limited settings like smart devices connected to the IoT. To address this, a novel encryption method for medical images that operates at the bit-plane level, tailored for IoT environments, is developed. The approach initializes by processing the original image through the Secure Hash Algorithm (SHA-512) to derive the initial conditions for the Chen chaotic map. Using the Chen chaotic system, three random number vectors are generated. The first two vectors are employed to shuffle each bit plane of the plaintext image, rearranging rows and columns. The third vector is used to create a random matrix, which further diffuses the permuted bit planes. Finally, the bit planes are combined to produce the ciphertext image. For further security enhancement, this ciphertext is embedded into a carrier image, resulting in a visually secured output. To evaluate the effectiveness of our algorithm, various tests are conducted, including correlation coefficient analysis (C.C < 0 or negative), histogram analysis, key space ((10 90 ) 8 ) and sensitivity assessments, entropy evaluation (E(S) > 7.98), and occlusion analysis. These tests confirm the robustness and reliability of our encryption scheme in safeguarding medical images.