mlsanityData to 14 Oct 2026

Puppy: A Publicly Verifiable Watermarking Protocol

arXiv 2312.09125 ↗First posted 14 Dec 2023cs.CRcited by 2

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Abstract (arXiv)

In this paper, we propose Puppy, the first formally defined framework for converting any symmetric watermarking into a publicly verifiable one. Puppy allows anyone to verify a watermark any number of times with the help of an untrusted third party, without requiring owner presence during detection. We formally define and prove security of Puppy using the ideal/real-world simulation paradigm and construct two practical and secure instances: (1) Puppy-TEE that uses Trusted Execution Environments (TEEs), and (2) Puppy-2PC that relies on two-party computation (2PC) based on garbled circuits. We then convert four current symmetric watermarking schemes into publicly verifiable ones and run extensive experiments using Puppy-TEE and Puppy-2PC. Evaluation results show that, while Puppy-TEE incurs some overhead, its total latency is on the order of milliseconds for three out of four watermarking schemes. Although the overhead of Puppy-2PC is higher (on the order of seconds), it is viable for settings that lack a TEE or where strong trust assumptions about a TEE need to be avoided. We further optimize the solution to increase its scalability and resilience to denial of service attacks via memoization.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). First posted on arXiv 14 Dec 2023.

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  1. 2026VOW: Verifiable and Oblivious Watermark Detection for Large Language Models
  2. 2025PVMark: Enabling Public Verifiability for LLM Watermarking Schemes
  3. 2025PoLO: Proof-of-Learning and Proof-of-Ownership at Once with Chained Watermarking
  4. 2023Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
  5. 2026EmbTracker: Traceable Black-box Watermarking for Federated Language Models
  6. 2024The Good, the Bad and the Ugly: Meta-Analysis of Watermarks, Transferable Attacks and Adversarial Defenses
  7. 2024Forging the Unforgeable: On the Feasibility of Counterfeit Watermarks in Backdoor-Based Dataset Ownership Verification
  8. 2026ChainMark: Model-Free LLM Watermarking with Closed-Form Calibration