Faore Pony-inspired Chaotic Neural Encryption for Secure and Efficient Medical Image Protection
Year: 2025
Type: article
Abstract: The Faore Pony-Inspired Optimization for Chaotic Neural Encryption introduces a novel encryption approach for securing medical images in telemedicine applications. This framework leverages bio-inspired optimization, incorporating adaptive stamina-based key evolution and chaotic neural processing to enhance security and unpredictability. By integrating chaotic maps with an optimized pixel diffusion mechanism, the encryption scheme ensures high randomness, making it resistant to statistical and differential attacks. The proposed model disrupts structural correlations in medical images, preserving confidentiality while maintaining computational efficiency. The adaptive optimization mechanism dynamically refines encryption parameters, ensuring robustness against evolving security threats. The approach prioritizes secure transmission without compromising image integrity, making it well-suited for real-time healthcare environments. The framework’s resilience in preventing unauthorized access strengthens data protection in medical imaging systems. This study contributes to the development of enhanced encryption models for digital healthcare, ensuring secure, reliable, and efficient image transmission for modern telemedicine applications.
Author: Journal of Theoretical and Applied Information Technology
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7103657276
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