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Medical image security using optimized chaotic affine assisted elliptic curve signcryption
Gogineni Krishna Chaitanya1, Sujatha Gorinta1
1Department of Computer Science & Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Andhra Pradesh 522302, India.
Computational Biology and Chemistry
|August 14, 2026
Summary
This study introduces an optimized chaotic affine-assisted Elliptic Curve Cryptography (ECC) method for secure medical image transmission. The new approach enhances security and efficiency in digital medical imaging systems.
Area of Science:
- Computer Science
- Cryptography
- Medical Imaging
Background:
- Multimedia data security is crucial, especially for medical images transmitted over unreliable networks.
- Existing medical image encryption methods face challenges like security vulnerabilities, complex key generation, high error rates, and computational demands.
Purpose of the Study:
- To develop an efficient and secure medical image protection system.
- To address the limitations of current encryption techniques using an optimized chaotic affine-assisted Elliptic Curve Cryptography (OCAEC) approach.
Main Methods:
- Image signcryption using OCAEC with optimized keys from the Fruit Fly Optimization algorithm.
- Image fragmentation into shares using the E-Secrete Picture Sharing Scheme (ESPSS).
- Pixel distortion via chaotic Arnold's cat map and scrambling using affine transformation, followed by unsigncryption.
Main Results:
- High encryption performance: NPCR (99.71%), UACI (33.45%), entropy (7.99).
- Efficient processing times: Encryption (0.1245s), Decryption (0.0982s).
- Excellent image reconstruction: PSNR (65.12dB), SSIM (0.9645), low MSE (0.02).
Conclusions:
- The proposed OCAEC method offers a robust and efficient solution for medical image security.
- The system demonstrates superior performance and security compared to existing methods through rigorous testing.
- The approach effectively balances security, efficiency, and image integrity for digital medical data.