ORIGINAL RESEARCH article

Front. Comput. Neurosci.

Volume 19 - 2025 | doi: 10.3389/fncom.2025.1591972

This article is part of the Research TopicAdvancements in Smart Diagnostics for Understanding Neurological Behaviors and Biosensing ApplicationsView all 10 articles

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

Provisionally accepted

The final, formatted version of the article will be published soon.

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.

Keywords: image encryption, Chen chaotic map, Chaos, Meaningful encryption, Bit-level encryption, IoT

Received: 11 Mar 2025; Accepted: 14 May 2025.

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