To address the security risk caused by fixed offset mapping and the limited recoverability of random mapping used in image watermarking, we propose an image self-embedding fragile watermarking algorithm based on deneighborhood mapping. First, the image is divided into several 2*2 blocks, and authentication watermark and recovery watermark are generated based on the average value of the image blocks. Then, the denighborhood mapping is implemented as, for each image block, its mapping block is randomly selected outside it's neighborhood whose size is specified by a parameter. Finally, the authentication watermark and the recovery watermark are embedded in the image block itself and its corresponding mapping block. Theoretical analysis indicates that in the case of continuous region tampering, the proposed watermarking method can achieve better the recovery rate of the tampered image block than the method based on the random mapping. The experimental results verify the rationality and effectiveness of the theoretical analysis. Moreover, compared with the existing embedding algorithms based on random mapping, chaos mapping and Arnold mapping, in the case of continuous region tampering, the average recovery rate of the tampered region achieved by the proposed algorithm is higher.
TRLG: Fragile blind quad watermarking for image tamper detection and recovery by providing compact digests with quality optimized using LWT and GA
Ferdowsi University of Mashhad（马什哈德费尔多西大学）；Computer Engineering Department（计算机工程系）；Computer Engineering Department, Ferdowsi University of Mashhad（马什哈德费尔多西大学计算机工程系）
Block Based Medical Image Watermarking Technique for Tamper Detection and Recovery
本文提出了一种新的基于脆弱块的医学图像水印技术，该技术能够在医学图像中嵌入患者数据，验证感兴趣区域（Region of Interest，ROI）的完整性，检测ROI内的篡改块，并利用较少的认证和恢复数据和简单的数学计算恢复原始ROI。在该方法中，医学图像分为三个区域，称为ROI，RONI（非感兴趣区域）和边界像素。然后，利用行程长度编码（RLE）技术对感兴趣区（ROI）和电子病历（EPR）的认证数据进行压缩，并嵌入到感兴趣区中。ROI的恢复信息嵌入RONI内部，ROI的信息嵌入边界像素。在多幅医学图像上的实验结果表明，该方法能够产生高质量的水印医学图像，并能识别出水印医学图像ROI内的篡改区域，恢复出原始ROI。
Bit-Level Triangular Content-Aware Permutation for Fragile Image Watermarking: Zero False Positive Rate, Single-Bit Sensitivity, and Arbitrary Dimension Support
Amirkabir University of Technology (Tehran Polytechnic)（阿米尔卡比尔理工大学（德黑兰理工大学））；Iran University of Science and Technology（伊朗科技大学）
ShapeMark: Robust and Diversity-Preserving Watermarking for Diffusion Models
Institute of Information Engineering, Chinese Academy of Sciences（中国科学院信息工程研究所）；School of Cyber Security, University of Chinese Academy of Sciences（中国科学院大学网络空间安全学院）；School of Cybersecurity, University of International Relations（国际关系学院网络安全学院）
Fragile Model Watermark for integrity protection: leveraging boundary volatility and sensitive sample-pairing
East China Normal University（华东师范大学）；Guangxi Normal University（广西师范大学）；Shenzhen Research Institute of Big Data, The Chinese University of Hong Kong（香港中文大学深圳大数据研究院）
RMCW: A Deletion-Robust Watermark Based on Reed--Muller Codes for Language Models
Tsinghua University（清华大学）；University of Wisconsin–Madison（威斯康星大学麦迪逊分校）；Shanghai Qi Zhi Institute（上海期智研究院）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））；Chinese Academy of Sciences（中国科学院）；Xiongan AI Institute（雄安人工智能研究院）
