Image Encryption and Compression Based on Reversed Diffusion Model

Nowadays, as critical conduits of communication, the information security of images and videos is particularly important. The existing encryption techniques usually transform images into high-frequency content that resembles noise, pre-senting significant challenges in achieving efficient compression. This paper presents an innovative collaborative approach that integrates image encryption and compression using a reversed diffusion model. This method, by reversing the typical process of diffusion models, adeptly changes encrypted high-frequency content into a domain that is more amenable to compression. Leveraging the reversible nature of the Denoising Diffusion Implicit Models (DDIM), our framework ensures the high-fidelity restoration of information. Our experimental findings demonstrate that this approach not only effectively encrypts images but also compresses the encrypted high-frequency noise content, outperforming Video Versatile Coding (VVC) in compression performance.