Enhancing medical image privacy in IoT with bit-plane level encryption using chaotic map
Asiri F. Al Malwi W. Zhukabayeva T. Nafea I. Aziz A. Gazem N.A. Qayyum A.
2025Frontiers Media SA
Frontiers in Computational Neuroscience
2025#19
Introduction: 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. Methods: The approach initializes by processing the original image through the Secure Hash Algorithm (SHA) 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. Results: To evaluate the effectiveness of our algorithm, various tests are conducted, including correlation coefficient analysis (C.C < or negative), histogram analysis, key space [(1090)8] and sensitivity assessments, entropy evaluation [E(S) > 7.98], and occlusion analysis. Conclusion: Extensive evaluations have proven that the designed scheme exhibits a high degree of resilience to attacks, making it particularly suitable for small IoT devices with limited processing power and memory. Copyright
bit-level encryption , chaos , Chen chaotic map , image encryption , IoT , meaningful encryption
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Informatics and Computer Systems Department, College of Computer Science, King Khalid University, Abha, Saudi Arabia
Department of Information Systems, L.N. Gumilyov Eurasian National University, Astana, Kazakhstan
College of Computer Science and Engineering, Taibah University, Medina, Saudi Arabia
High Performance Computing Centre North, Umeå University, Västerbotten, Umeå, Sweden
Department of Information Systems, College of Business Administration-Yanbu, Taibah University, Medina, Saudi Arabia
6G Lab, School of Engineering and Informatics, University of Sussex, Brighton, United Kingdom
Informatics and Computer Systems Department
Department of Information Systems
College of Computer Science and Engineering
High Performance Computing Centre North
Department of Information Systems
6G Lab
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