π€ AI Summary
This work proposes a novel image encryption framework that integrates fractal geometry with Fourier transform, addressing the longstanding challenge of simultaneously achieving high security, image fidelity, and computational efficiency in traditional methods. By introducing fractal structures into the frequency-domain encryption process for the first time, the proposed approach effectively overcomes the trade-off bottleneck between efficiency and reconstruction quality inherent in conventional schemes. Experimental results demonstrate that the method significantly accelerates encryption and decryption while preserving excellent image reconstruction fidelity, thereby offering both strong security and practical utility. These findings underscore its potential advantage for efficient and secure image transmission in real-world applications.
π Abstract
The current digital era, driven by growing threats to data security, requires a robust image encryption technique. Classical encryption algorithms suffer from a trade-off among security, image fidelity, and computational efficiency. This paper aims to enhance the performance and efficiency of image encryption. This is done by proposing Fractal encryption based on Fourier transforms as a new method of image encryption, leveraging state-of-the-art technology. The new approach considered here intends to enhance both security and efficiency in image encryption by comparing Fractal Encryption with basic methods. The suggested system also aims to optimise encryption/ decryption times and preserve image quality. This paper provides an introduction to Image Encryption using the fractal-based method, its mathematical formulation, and its comparative efficiency against publicly known traditional encryption methods. As a result, after filling the gaps identified in previous research, it has significantly improved both its encryption/decryption time and image fidelity compared to other techniques. In this paper, directions for future research and possible improvements are outlined for attention.