Enhancing Image Encryption Security via Metaheuristic-Optimized Logistic Chaotic Mapping

With the increasing reliance on digital communication, robust image encryption has become essential to protect sensitive data from unauthorized access. This paper presents a novel chaos-based image encryption technique that enhances security by dynamically adapting the logistic chaotic map to the input image’s characteristics. Unlike conventional chaotic encryption methods—which generate static pseudo-random sequences irrespective of the plain-image—our approach employs the Harmony Search (HS) metaheuristic algorithm to intelligently optimize the logistic map’s parameters. This optimization ensures that the chaotic sequences are uniquely tailored to each image, significantly improving key sensitivity and maximizing Shannon entropy in the cipher-image. The proposed method offers a versatile solution for real-world applications, including secure medical imaging, confidential military communications, and privacy-preserving cloud storage. Rigorous security analyses, including statistical tests, differential attack resistance, and key space evaluation, demonstrate the algorithm’s superiority over existing schemes in terms of both robustness and efficiency.