首页|PR3: Reversible and Usability-Enhanced Visual Privacy Protection via Thumbnail Preservation and Data Hiding

PR3: Reversible and Usability-Enhanced Visual Privacy Protection via Thumbnail Preservation and Data Hiding

扫码查看
原文链接
  • NETL
  • NSTL
  • IEEE
The image hosting platform is becoming increasingly popular due to its user-friendly features, but it is prone to causing privacy concerns. Only protecting privacy, in fact, can be easy to come true, but usability is frequently sacrificed. Visual privacy protection schemes aim to make a balance between privacy and usability, whereas they are often irreversible. Recently, some reversible visual privacy protection schemes have been proposed by preserving thumbnails (known as TPE). However, they either have excessive states in the Markov chain modeled by the scheme or cannot reverse losslessly. Meanwhile, images encrypted by existing TPE schemes can not embed additional information and thus the usability is limited to visual observation. In view of this, we pertinently propose a reversible and usability-enhanced visual privacy protection scheme (called PR3) based on thumbnail preservation and data hiding. In this scheme, we utilize the sum-preserving data embedding algorithm to substitute the the lowest seven bits of the image without changing the sum. Any data overflow resulting from the above process is stored in the vacated space of the most significant bits. The remaining space serves two purposes: embedding additional information and adjusting the image to approximate the thumbnail. Compared with existing TPE works, PR3 has fewer states in the Markov chain and supports lossless recovery of images. In addition, additional information can be embedded in the encrypted image to enhance usability.

PrivacyVisualizationUsabilityEncryptionVectorsImage codingHistograms

Ruoyu Zhao、Yushu Zhang、Wenying Wen、Xinpeng Zhang、Xiaochun Cao、Yong Xiang

展开 >

College of Computer Science and Technology, Nanjing University of Aeronautics and Astronautics, Nanjing, China

School of Information Technology, Jiangxi University of Finance and Economics, Nanchang, China

School of Computer Science, Fudan University, Shanghai, China

School of Cyber Science and Technology, Sun Yat-sen University, Shenzhen, China

School of Information Technology, Deakin University, Burwood, Victoria, Australia

展开 >

2025

10.1109/TBDATA.2024.3375155

IEEE transactions on big data

IEEE transactions on big data

ISSN：
年,卷(期)：2025.11(1)
  • 38