Content and Privacy Protection in JPEG Images by Reversible Visual Transformation
Source abstract
Abstract
With the popularity of cloud computing and social networks, more and more JPEG images are stored and distributed. Consequently, how to protect privacy and content in JPEG images has become an important issue. Although traditional encryption schemes can be employed, the file format of JPEG images is changed so that their usage may be affected. In this paper, a reversible visual transformation algorithm is proposed to protect content in JPEG images. Specifically, the DC coefficient in each user-selected block is modified, while the information required to recover it is reversibly hidden into AC coefficients. Then the signs of AC coefficients in the selected blocks are flipped and the blocks are further scrambled with a secret key. By embedding the location information of the selected blocks in a transformed image, the original image can be exactly recovered when needed. Besides, regions to be protected can be arbitrarily chosen without substantially affecting the rest of the image. The experimental results on a set of JPEG images validate the efficacy and reversibility of the proposed algorithm. In addition, good performance is achieved in terms of invisibility of the protected content, image quality, file size preservation and security.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Steganography and Watermarking Techniques · Chaos-based Image/Signal Encryption · Digital Media Forensic Detection
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Computer Science and Engineering, South China University of Technology, Guangzhou 510006, China
Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong, China
Funding
National Natural Science Foundation of China · Guangdong Province Key Area R&D Program of China
References (25)
Show source-provided references
1. The JPEG still picture compression standard10.1109/30.125072 ↗
2. Norcen, R., and Uhl, A. (2003, January 2–3). Selective encryption of the JPEG2000 Bitstream. Proceedings of the Communications and Multimedia Security, Advanced Techniques for Network and Data Protection, CMS2003, LNCS, Torino, Italy.10.1007/978-3-540-45184-6_16 ↗
3. Korshunov, P., and Ebrahimi, T. (2013, January 27–30). Using face morphing to protect privacy. Proceedings of the 2013 10th IEEE International Conference on Advanced Video and Signal Based Surveillance, Krakow, Poland.10.1109/AVSS.2013.6636641 ↗
4. Korshunov, P., and Ebrahimi, T. (2013, January 1–3). Using warping for privacy protection in video surveillance. Proceedings of the 2013 18th International Conference on Digital Signal Processing, Fira, Greece.10.1109/ICDSP.2013.6622791 ↗
5. Scrambling–embedding for JPEG compressed image10.1016/j.sigpro.2014.10.028 ↗
6. Yuan, L., and Ebrahimi, T. (2015, January 27–30). Image transmorphing with JPEG. Proceedings of the 2015 IEEE International Conference on Image Processing (ICIP), Quebec City, QC, Canada.10.1109/ICIP.2015.7351547 ↗
7. Li, W., Ni, R., and Zhao, Y. (2017). JPEG photo privacy-preserving algorithm based on sparse representation and data hiding. International Conference on Image and Graphics, Springer.10.1007/978-3-319-71598-8_51 ↗
8. Fully reversible privacy region protection for cloud video surveillance10.1109/TCC.2015.2469651 ↗
9. Reversible data hiding based compressible privacy preserving system for color image10.1007/s11042-017-5230-8 ↗
10. Niimi, M., Masutani, F., and Noda, H. (2012, January 4–7). Protection of privacy in JPEG files using reversible information hiding. Proceedings of the 2012 International Symposium on Intelligent Signal Processing and Communications Systems, Taipei, Taiwan.10.1109/ISPACS.2012.6473530 ↗
11. Ra, M.-R., Govindan, R., and Ortega, A. (2013, January 2–5). P3: Toward privacy-preserving photo sharing. Proceedings of the 10th USENIX Symposium on Networked Systems Design and Implementation, Lombard, IL, USA.
12. Yuan, L., Korshunov, P., and Ebrahimi, T. (2015, January 4–8). Secure JPEG scrambling enabling privacy in photo sharing. Proceedings of the 2015 11th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition, Ljubljana, Slovenia.10.1109/FG.2015.7285022 ↗
13. JPEG-based scalable privacy protection and image data utility preservation10.1049/iet-spr.2017.0413 ↗
14. Coltuc, D. (October, January 16). Improved capacity reversible watermarking. Proceedings of the 2007 IEEE International Conference on Image Processing, San Antonio, TX, USA.10.1109/ICIP.2007.4379293 ↗
15. Reversible data hiding in JPEG images10.1109/TCSVT.2015.2473235 ↗
16. A reversible visual transformation algorithm for JPEG images
17. Daemen, J., and Rijmen, V. (2002). The Design of Rijndael: AES—The Advanced Encryption Standard, Springer.10.1007/978-3-662-04722-4_1 ↗
18. Ciftci, S., Akyuz, A.O., and Ebrahimi, T. (2017). A reliable and reversible image privacy protection based on false colors. IEEE Trans. Multimed.10.1109/TMM.2017.2728479 ↗
19. Westfeld, A. (2001, January 25–27). F5—A steganographic algorithm: High capacity despite better steganalysis. Proceedings of the International Workshop on Information Hiding, Pittsburgh, PA, USA.10.1007/3-540-45496-9_21 ↗
20. Wu, H., and Huang, J. (2011, January 11–14). Secure JPEG steganography by LSB+ matching and multi-band embedding. Proceedings of the 2011 18th IEEE International Conference on Image Processing, Brussels, Belgium.
21. Rivest, R.L. (1992). The MD5 Message-Digest Algorithm, MIT Laboratory for Computer Scienceand RSA Data Security, Inc.. RFC Editor.10.17487/rfc1321 ↗
22. (2020, September 22). Brute Force, Wikipedia. Available online: http://en.wikipedia.org/wiki/Brute_force_attack.
23. Image camouflage by reversible image transformation10.1016/j.jvcir.2016.06.018 ↗
24. Wang, K., Lu, Z., and Hu, Y. (2013). A high capacity lossless data hiding scheme for JPEG images. J. Syst. Softw.10.1016/j.jss.2013.03.083 ↗
25. Gallagher, A., and Chen, T. (2009, January 20–25). Understanding groups of images of people. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Miami, FL, USA.10.1109/CVPRW.2009.5206828 ↗