Protection of Images and Neural Networks

Digital images play a pivotal role in modern communication, documentation, and creative expression, serving as powerful visual tools that convey information, emotions, and ideas across diverse platforms and audiences. Image protection is vital as it ensures creators receive fair recognition and compensation, while deterring illegal copying and distribution that undermines their livelihood. On the other hand, neural network model is a new type of data which grows rapidly in recent years and is widely used. Compared with digital images, neural network model has complex structure, wide variety and large number of parameters. For this reason, image protection methods cannot be used for neural network model directly. Therefore, develop new schemes for neural networks is necessary.

Topics of this special session including but not limited to:
Image Watermarking
Perceptual Image Hashing
Image Steganography
Image Steganalysis
Image Forensics
Neural Network Watermarking
Neural Network Steganography

Please choose Special Session 1 to submit: https://www.zmeeting.org/submission/AAIP2026

Organizer
Assoc. Prof. Zichi Wang, Shanghai University, China

Zichi Wang received the BS degree in electronics and information engineering from Shanghai University, China, in 2014, and received the MS degree in signal and information processing in 2017, the PhD degree in information and communication engineering from the same university in 2020. He is currently with the School of Communication and Information Engineering, Shanghai University, Shanghai, as an Associate professor. His research interests include steganography, steganalysis, and artificial intelligence security. He has published over 100 papers in these areas.

Co-organizers

Asst. Prof. Weixiang Li, Shenzhen University, China

Weixiang Li received the B.S. degree from Xidian University (XDU), Xi’an, China, in 2016, and the Ph.D. degree from the University of Science and Technology of China (USTC), Hefei, China, in 2021. He is currently an Assistant Professor with the College of Electronics and Information Engineering, Shenzhen University (SZU), Shenzhen, China. His research interests include information hiding and multimedia forensics. He was a recipient of the Best Student Paper Award at the Sixth ACM IH&MMSec in 2018.

 

Lecturer Xinran Li, Shanghai Business School, China

Xinran Li received the B.S. degree in electrical engineering and the M.S. degree in mechanical engineering from Hebei Agricultural University, Hebei, China. In 2015 and 2017, respectively, and the Ph.D. degree in control engineering from the University of Shanghai for Science and Technology, Shanghai, China, in 2023. She is currently with the Faculty of Business Information, Shanghai Business School, Shanghai, as a Lecturer. She has authored or coauthored more than 30 articles in her research field, which include multimedia security, image hashing, and information hiding.