Position: 3D Gaussian Splatting Watermarking Should Be Scenario-Driven and Threat-Model Explicit
Yangfan Deng, Anirudh Nakra, Min Wu

TL;DR
This paper emphasizes the importance of scenario-driven security models for watermarking 3D Gaussian Splatting assets, proposing a framework that aligns security objectives with realistic threat scenarios to improve IP protection.
Contribution
It introduces a scenario-driven security formulation and a reference framework for 3D watermarking, addressing gaps in security specification and evaluation for 3D content.
Findings
Analyzes legacy spread-spectrum watermarking scheme
Highlights trade-offs in watermarking design choices
Proposes a formal threat model for 3D watermarking
Abstract
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…
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Taxonomy
TopicsAdvanced Steganography and Watermarking Techniques · Physical Unclonable Functions (PUFs) and Hardware Security · Adversarial Robustness in Machine Learning
