MLVPP: Multilevel Visual Privacy Protection via Thumbnail Preservation and Key Sharing

Nowadays, shared social images often contain multiple privacy subjects, and the disclosure of these privacy subjects increases the risk of privacy violations; thus, the protection of visual privacy is particularly important. However, existing means of visual privacy protection render images unavailable and are typically protected only for images with a single privacy subject. Combining compressed sensing (CS) and 2DCS, this article proposes a multilevel visual privacy protection scheme (MLVPP) via thumbnail preservation (TPE) and key sharing (KS), which includes two stages, that is, CS-TPE multilevel encryption and KS multilevel decryption. In the first stage, we utilize 2DCS to enable the compressed sampled observations to preserve the structural similarity of the nonsensitive part and leverage CS to encrypt multiple sensitive parts of the image. The CS-processed image is then made to strike a good balance between privacy and availability through TPE. In the second stage, with the help of KS mechanism, the CS encryption keys and TPE key are shared in different combinations with the users related to the privacy subjects for meeting the MLVPP requirements. The quality of decrypted images varies for different classes of related users, e.g., unrelated users, semirelated users, and full-related users. The proposed approach preserves the visual information in the nonsensitive part of the image while providing security for the sensitive parts. Compared with related works, MLVPP reveals that the PSNR of the fully decrypted image can reach 34.04, and the SSIM is greater than 0.96 at a compression rate of 0.25. Experimental results demonstrate the superior performance of MLVPP.

I. Introduction

As internet technology continues to evolve, the sharing of social images containing multiple privacy subjects has brought great convenience to humanity, but it has also exacerbated privacy risks [1]. Privacy protection is aimed at individuals who wish to prevent data that are considered privacy sensitive from entering the public domain. If these data are images or videos, it is called visual privacy protection [2], which aims to balance usability and privacy security on visual content. When sharing an image containing multiple privacy subjects, it is easy to implement encryption of privacy subjects, while the difficulty lies in providing different levels of protection for different relevant users as well as not sacrificing usability.