Image Disguise based on Generative Model

TL;DR

This paper introduces a novel image encryption technique that disguises images as visually similar but content-independent images using generative models, enhancing security and reducing visual clues of encryption.

Contribution

The paper proposes a new image disguise method leveraging generative models to produce visually identical images that conceal original content and improve security.

Findings

Successfully generates visually similar images that obscure original content.

Reduces visual signs of encryption compared to traditional methods.

Enhances security by making encrypted images indistinguishable from normal images.

Abstract

To protect image contents, most existing encryption algorithms are designed to transform an original image into a texture-like or noise-like image, which is, however, an obvious visual sign indicating the presence of an encrypted image, results in a significantly large number of attacks. To solve this problem, in this paper, we propose a new image encryption method to generate a visually same image as the original one by sending a meaning-normal and independent image to a corresponding well-trained generative model to achieve the effect of disguising the original image. This image disguise method not only solves the problem of obvious visual implication, but also guarantees the security of the information.