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EmMark: Robust Watermarks for IP Protection of Embedded Quantized Large Language Models

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arxiv 2402.17938 v1 pith:XKKRTX4G submitted 2024-02-27 cs.CR cs.CL

classification cs.CRcs.CL
keywords emmarkmodelmodelswatermarkembeddedlanguagelargeachieving
verification ladder T0 review T1 audit T2 compute T3 formal
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This paper introduces EmMark,a novel watermarking framework for protecting the intellectual property (IP) of embedded large language models deployed on resource-constrained edge devices. To address the IP theft risks posed by malicious end-users, EmMark enables proprietors to authenticate ownership by querying the watermarked model weights and matching the inserted signatures. EmMark's novelty lies in its strategic watermark weight parameters selection, nsuring robustness and maintaining model quality. Extensive proof-of-concept evaluations of models from OPT and LLaMA-2 families demonstrate EmMark's fidelity, achieving 100% success in watermark extraction with model performance preservation. EmMark also showcased its resilience against watermark removal and forging attacks.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. Invariant-based Robust Weights Watermark for Large Language Models

    cs.CR 2025-07 conditional novelty 4.0 of 10

    An invariant-based weights watermark embeds per-user keys into the null space of transformer invariants and uses noise to repel collusion.

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