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Yiran HAN, Jianwei LIU, Xin DENG, et al., “Confidential Image Super-resolution with Privacy Protection,” Chinese Journal of Electronics, vol. x, no. x, pp. 1–11, xxxx doi: 10.23919/cje.2023.00.034
Citation: Yiran HAN, Jianwei LIU, Xin DENG, et al., “Confidential Image Super-resolution with Privacy Protection,” Chinese Journal of Electronics, vol. x, no. x, pp. 1–11, xxxx doi: 10.23919/cje.2023.00.034

Confidential Image Super-resolution with Privacy Protection

doi: 10.23919/cje.2023.00.034
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  • Author Bio:

    Yiran HAN received the B.E. degree in Software college of Northeastern University, China, in 2019. She currently is studing for a doctor’s degree in School of Cyber Science and Technology, Beihang University, Beijing, China. Her research direction focuses on privacy protection, artificial intelligence security, information security, computer network security, and cryptographic protocol design. (Email: hanyiran@buaa.edu.cn)

    Jianwei LIU (Senior Member, IEEE) received the Ph.D. in communication engineering from Xidian University, China in 1998, and his B.S. and M.S. degrees in electronic engineering from Shandong University, China in 1985 and 1988. He is currently a professor and dean of School of Cyber Science and Technology, Beihang University. His current research interests include cryptographic protocol design, security on wireless and mobile network, computer network security, and Cryptography. He has published 6 books and more than 200 papers in his research fields. He is a senior member of the Chinese Institute of Electronics, and director of the Chinese Association for Cryptologic Research, and member of Teaching steering committee of information security of MOE, China. He has been awarded the first prize of technological invention of China. (Email: liujianwei@buaa.edu.cn)

    Xin DENG (Member, IEEE) received the master’s degree in electrical information engineering from Beihang University, Beijing, China, in 2016, and the PhD degree in electrical and electronic engineering from Imperial College London, London, U.K., in March 2020. She is currently an associate professor with the Department of Cyber Science and Technology, Beihang University, Beijing, China. Her research interests include sparse coding with applications in image and video processing, machine learning, and multimodal signal processing. (Email: cindydeng@buaa.edu.cn)

    Junpeng JING received the BS degree from Beihang University (BUAA), Beijing, China, in July 2020. He is currently working toward the MS degree with the School of Cyber Science and Technology, Beihang University, Beijing, China.He was awarded three academic scholarships from Beihang University, including a national scholarship. His research interests include image hiding and reversible image conversion. (Email: junpengjing@buaa.edu.cn)

    Yanting ZHANG received Ph.D. degree in Communication and Information System, Beihang University, 2023. She is currently an engineer in China Electronics Standardization Institute. Her research interests include artificial intelligence security, cryptography, information security and privacy. (Email: zhangyanting@cesi.cn)

  • Corresponding author: Email: cindydeng@buaa.edu.cn
  • Available Online: 2024-03-20
  • Nowadays, people are getting used to upload images to a third-party for post-processing, such as image denoising and super-resolution. However, this may easily lead to the disclosure of the privacy in the confidential images. One possible solution is to encrypt the image before sending it to the third party, however, the encrypted image can be easily detected by a malicious attacker in the transmission channel. In this paper, we propose a confidential image super-resolution method namely HSR-Net, which firstly hide the secret image and then super-resolve it in the hidden domain. The HSR-Net is composed of three important modules: image hiding module (IHM), image super-resolution module (ISM), and image revealing module (IRM). The IHM aims to encode secret image and hide it into a cover image to generate the stego image. The stego image looks similar to the cover image but contains the information of the secret image. Then, the third party uses the ISM to perform image super-resolution on the stego image. After that, the user can reveal the super-resolved secret image from the stego image. Our HSR-Net has two advantages. Firstly, it ensures that the third party cannot not directly operate on the secret image to protect the user’s privacy. In addition, due to the similarity between the stego image and cover image, we can reduce the attacker’s suspicion to further improve the image security. The experimental results on various datasets, including DIV2K dataset and Flickr2K dataset. The PSNR of IHM is 38.81dB, the PSNR of ISM is 28.91 dB, and the PSNR of IRM is 23.51 dB, which verify that our HSR-Net is able to achieve image super-resolution and protect user’s privacy simultaneouly.
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