The advent of video-based Large Language Models (LLMs) has significantly enhanced video understanding. However, it has also raised some safety concerns regarding data protection, as videos can be more easily annotated, even without authorization. This paper introduces Video Watermarking, a novel technique to protect videos from unauthorized annotations by such video-based LLMs, especially concerning the video content and description, in response to specific queries. By imperceptibly embedding watermarks into key video frames with multi-modal flow-based losses, our method preserves the viewing experience while preventing misuse by video-based LLMs. Extensive experiments show that Video Watermarking significantly reduces the comprehensibility of videos with various video-based LLMs, demonstrating both stealth and robustness. In essence, our method provides a solution for securing video content, ensuring its integrity and confidentiality in the face of evolving video-based LLMs technologies.
FreqMark: Invisible Image Watermarking via Frequency Based Optimization in Latent Space
University of California, Santa Cruz(加州大学圣克鲁兹分校);The University of Hong Kong(香港大学);University of Science and Technology of China(中国科学技术大学);IEG, Tencent(腾讯IEG);Fudan University(复旦大学)
Safeguarding Medical Image Segmentation Datasets against Unauthorized Training via Contour- and Texture-Aware Perturbations
Beihang University(北京航空航天大学);Nanyang Technological University(南洋理工大学);Memorial Sloan Kettering Cancer Center(纪念斯隆凯特琳癌症中心);Great Bay University(大湾区大学);Beijing Institute of Technology(北京理工大学)
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))
Protecting Your Video Content: Disrupting Automated Video-based LLM Annotations
Tsinghua University(清华大学);ByteDance(字节跳动);Digital Center, China Merchants Group Limited(招商银行集团数字中心);Shenzhen University(深圳大学);Peng Cheng Laboratory(鹏城实验室)
LVMark: Robust Watermark for Latent Video Diffusion Models
Department of Artificial Intelligence, Korea University, Seoul 02841, Republic of Korea(人工智能系,韩国大学,首尔02841,大韩民国);Google DeepMind, Mountain View, CA 94043, USA(谷歌DeepMind,山景城,加利福尼亚州94043,美国)