AI-generated content has accelerated the topic of media synthesis, particularly Deepfake, which can manipulate our portraits for positive or malicious purposes. Before releasing these threatening face images, one promising forensics solution is the injection of robust watermarks to track their own provenance. However, we argue that current watermarking models, originally devised for genuine images, may harm the deployed Deepfake detectors when directly applied to forged images, since the watermarks are prone to overlap with the forgery signals used for detection. To bridge this gap, we thus propose AdvMark, on behalf of proactive forensics, to exploit the adversarial vulnerability of passive detectors for good. Specifically, AdvMark serves as a plug-and-play procedure for fine-tuning any robust watermarking into adversarial watermarking, to enhance the forensic detectability of watermarked images; meanwhile, the watermarks can still be extracted for provenance tracking. Extensive experiments demonstrate the effectiveness of the proposed AdvMark, leveraging robust watermarking to fool Deepfake detectors, which can help improve the accuracy of downstream Deepfake detection without tuning the in-the-wild detectors. We believe this work will shed some light on the harmless proactive forensics against Deepfake.
All in One: Unifying Deepfake Detection, Tampering Localization, and Source Tracing with a Robust Landmark-Identity Watermark
School of Computer Science and Technology, Xinjiang University, Urumqi, China（新疆大学计算机科学与技术学院）；Xinjiang Multimodal Intelligent Processing and Information Security Engineering Technology Research Center, Urumqi, China（新疆多模态智能处理与信息安全工程技术研究中心）
OmniGuard: Hybrid Manipulation Localization via Augmented Versatile Deep Image Watermarking
School of Electronic and Computer Engineering, Peking University（北京大学电子与计算机工程学院）；Peking University Shenzhen Graduate School-Rabbitpre AIGC Joint Research Laboratory（北京大学深圳研究生院Rabbitpre AIGC联合研究实验室）；School of Arts, Peking University（北京大学艺术学院）
Whether, Which, and Whose: Solving the Triple Challenge of Deepfake Proactive Forensics in Multi-Face Scenarios
College of Computer Science and Technology（计算机科学与技术学院）；Xinjiang University（新疆大学）；College of Computer Science and Electronic Engineering（计算机科学与电子工程学院）；Hunan University（湖南大学）
GIFGuard: Proactive Forensics against Deepfakes in Facial GIFs via Spatiotemporal Watermarking
School of Computer Science and Technology, Xinjiang University（新疆大学计算机科学与技术学院）；College of Computer Science and Electronic Engineering, Hunan University（湖南大学计算机科学与电子工程学院）
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）
Tell-Tale Watermarks for Explanatory Reasoning in Synthetic Media Forensics
Information and Society Research Division, National Institute of Informatics（信息与社会研究部，国家信息研究所）；Graduate School of Information Science and Technology, University of Tokyo（东京大学信息科学与技术研究生院）
CSGuard: Toward Forgery-Resistant Watermarking in Diffusion Models via Compressed Sensing Constraint
University of Science and Technology of China（中国科学技术大学）；Institute of Artificial Intelligence, Hefei Comprehensive National Science Center（人工智能研究所，合肥国家科学中心）；Lenovo Research（联想研究院）
An Efficient and Effective Watermarking Scheme for the Protection of the Intellectual Property Rights of Video Generative Models
Sun Yat-sen University（中山大学）；Guangdong Provincial Key Laboratory of Information Security Technology（广东省信息安全技术重点实验室）；University of Florence（佛罗伦萨大学）；University of Siena（锡耶纳大学）；Qilu University of Technology (Shandong Academy of Sciences)（齐鲁工业大学（山东省科学院））
Protect-Your-IP: Scalable Source-Tracing and Attribution against Personalized Generation
School of Electronic and Computer Engineering, Peking University（北京大学电子与计算机工程学院）；School of Computer Science and Technology, Harbin Institute of Technology (Shenzhen)（哈尔滨工业大学（深圳）计算机科学与技术学院）；Peking University Shenzhen Graduate School-Rabbitpre AIGC Joint Research Laboratory（北京大学深圳研究生院-Rabbitpre AIGC联合实验室）
Beyond Generation: Using Multimodal LLMs as Detectors of LLM-Generated Deepfake Facial Images
Institute of Cyber Security for Society (iCSS)（社会网络安全研究所（iCSS））；School of Computing, University of Kent（肯特大学计算学院）；London and South East University Group（伦敦与东南大学集团）
