3D content acquisition and creation are expanding rapidly in the new era of machine learning and AI. 3D Gaussian Splatting (3DGS) has become a promising high-fidelity and real-time representation for 3D content. Similar to the initial wave of digital audio-visual content at the turn of the millennium, the demand for intellectual property protection is also increasing, since explicit and editable 3D parameterization makes unauthorized use and dissemination easier. In this position paper, we argue that effective progress in watermarking 3D assets requires articulated security objectives and realistic threat models, incorporating the lessons learned from digital audio-visual asset protection over the past decades. To address this gap in security specification and evaluation, we advocate a scenario-driven formulation, in which adversarial capabilities are formalized through a security model. Based on this formulation, we construct a reference framework that organizes existing methods and clarifies how specific design choices map to corresponding adversarial assumptions. Within this framework, we also examine a legacy spread-spectrum embedding scheme, characterizing its advantages and limitations and highlighting the important trade-offs it entails. Overall, this work aims to foster effective intellectual property protection for 3D assets.
GuardSplat: Efficient and Robust Watermarking for 3D Gaussian Splatting
School of Computer Science and Engineering, Sun Yat-sen University（中山大学计算机科学与工程学院）；School of Computing and Information Technology, Great Bay University（大湾区大学计算与信息技术学院）；Pazhou Lab (Huangpu)（琶洲实验室（黄埔））
Machine learning (ML) models are applied in an increasing variety of domains. The availability of large amounts of data and computational resources encourages the development of ever more complex and valuable models. These models are considered intellectual property of the legitimate parties who have trained them, which makes their protection against stealing, illegitimate redistribution, and unauthorized application an urgent need. Digital watermarking presents a strong mechanism for marking model ownership and, thereby, offers protection against those threats. This work presents a taxonomy i…
Identifying Appropriate Intellectual Property Protection Mechanisms for Machine Learning Models: A Systematization of Watermarking, Fingerprinting, Model Access, and Attacks
SBA Research（SBA研究中心）；Vienna University of Technology（维也纳工业大学）
X-SG$^2$S: Safe and Generalizable Gaussian Splatting with X-dimensional Watermarks
South China University of Technology（南方科技大学）；Shenzhen MSU-BIT University（深圳MSU-BIT大学）；Peking University（北京大学）；Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ)（广东省人工智能与数字经济实验室）；Harbin Institute of Technology（哈尔滨工业大学）
The availability of bandwidth for internet access is sufficient enough to communicate digital assets. These digital assets are subjected to various types of threats. [19] As a result of this, protection mechanism required for the protection of digital assets is of priority in research. The threat of current focus is unauthorized copying of digital assets which give boost to piracy. This under the copyright act is illegal and a robust mechanism is required to curb this kind of unauthorized copy. To safeguard the copyright digital assets, a robust digital watermarking technique is needed. The ex…
University of California, Berkeley（加州大学伯克利分校）；Columbia University（哥伦比亚大学）；Cornell University（康奈尔大学）；Anthropic；Oregon State University（俄勒冈州立大学）；Google DeepMind（谷歌DeepMind）；ETH Zurich（苏黎世联邦理工学院）；University of Wisconsin–Madison（威斯康星大学麦迪逊分校）；Carnegie Mellon University（卡内基梅隆大学）；University of California, San Diego（加州大学圣地亚哥分校）
The recent advent in the field of multimedia proposed a many facilities in transport, transmission and manipulation of data. Along with this advancement of facilities there are larger threats in authentication of data, its licensed use and protection against illegal use of data. A lot of digital image watermarking techniques have been designed and implemented to stop the illegal use of the digital multimedia images. This paper compares the robustness of three different watermarking schemes against brightness and rotation attacks. The robustness of the watermarked images has been verified on th…
In recent times, communication through the internet has tremendously facilitated the distribution of multimedia data. Although this is indubitably a boon, one of its repercussions is that it has also given impetus to the notorious issue of online music piracy. Unethical attempts can also be made to deliberately alter such copyrighted data and thus, misuse it. Copyright violation by means of unauthorized distribution, as well as unauthorized tampering of copyrighted audio data is an important technological and research issue. Audio watermarking has been proposed as a solution to tackle this iss…
Natural language processing (NLP) technology has shown great commercial value in applications such as sentiment analysis. But NLP models are vulnerable to the threat of pirated redistribution, damaging the economic interests of model owners. Digital watermarking technology is an effective means to protect the intellectual property rights of NLP model. The existing NLP model protection mainly designs watermarking schemes by improving both security and robustness purposes, however, the security and robustness of these schemes have the following problems, respectively: (1) Watermarks are difficul…
Audio Pirates: Black-box Audio Watermark Removal via Diffusion Priors
University of Houston（德克萨斯大学休斯敦分校）；Waseda University（早稻田大学）；University of Hawaii at Mānoa（夏威夷大学马诺阿分校）；Keio University（庆应大学）；The University of Electro-Communications（电通通信大学）
The rapid development of multimedia and internet allows for wide distribution of digital media data. It becomes much easier to edit, modify and duplicate digital information besides that, digital documents are also easy to copy and distribute, therefore it will be faced by many threats. It is a big security and privacy issue. Another problem with digital document and video is that undetectable modifications can be made with very simple and widely available equipment, which put the digital material for evidential purposes under question With the large flood of information and the development of…
Recently, a significant amount of interest has been developed in motivating physicians to use e-health technology (especially Electronic Medical Records (EMR) systems). An important utility of such EMR systems is: a next generation of Clinical Decision Support Systems (CDSS) will extract knowledge from these electronic medical records to enable physicians to do accurate and effective diagnosis. It is anticipated that in future such medical records will be shared through cloud among different physicians to improve the quality of health care. Therefore, right protection of medical records is imp…
Intentional or unintentional leakage of confidential data is undoubtedly one of the most severe security threats that organizations face in the digital era. The threat now extends to our personal lives: a plethora of personal information is available to social networks and smartphone providers and is indirectly transferred to untrustworthy third party and fourth party applications. In this work, we present a generic data lineage framework LIME for data flow across multiple entities that take two characteristic, principal roles (i.e., owner and consumer). We define the exact security guarantees…
Intellectual Property Protection for 3D Gaussian Splatting Assets: A Survey
Sydney AI Centre, The University of Sydney（悉尼人工智能中心，悉尼大学）；The University of Melbourne（墨尔本大学）；Mohamed bin Zayed University of Artificial Intelligence（莫莫迪·本·扎耶德人工智能大学）
RealSeal: Revolutionizing Media Authentication with Real-Time Realism Scoring
Institute for Clarity in Documentation（文献清晰度研究所）；Inria Paris-Rocquencourt（法国国家信息与自动化研究所巴黎-罗夸恩库尔中心）；Rajiv Gandhi University（拉吉夫·甘地大学）；Tsinghua University（清华大学）；Palmer Research Laboratories（帕尔默研究实验室）
Cryptanalysis of LDPC-Based Pseudorandom Error-Correcting Codes
Institute for Network Sciences and Cyberspace, BNRist, Tsinghua University（清华大学网络科学与网络空间研究院）；Institute for Advanced Study, Tsinghua University（清华大学高等研究院）；Zhongguancun Laboratory, Beijing, China（中关村实验室）；State Key Laboratory of Cryptography and Digital Economy Security, Tsinghua University（清华大学密码与数字经济安全国家重点实验室）；School of Cryptologic Science and Engineering, Shandong University（山东大学密码学科学与工程系）；Shandong Key Laboratory of Artificial Intelligence Security, Shandong University（山东大学人工智能安全山东省重点实验室）；National Financial Cryptography Research Center, Beijing, China（国家金融密码研究中心）；Shandong Institute of Blockchain, Shandong, China（山东省区块链研究院）
