Tracing Provenance and Detecting Tampering with Complementary LLM Watermarks
- URL: http://arxiv.org/abs/2608.12713v1
- Date: Thu, 13 Aug 2026 01:55:16 GMT
- Title: Tracing Provenance and Detecting Tampering with Complementary LLM Watermarks
- Abstract summary: Existing watermarks preserve provenance under editing, but this same robustness allows an adversary to alter critical content while retaining attribution.<n>We introduce an innovative watermark that jointly provides provenance and tamper evidence.<n>The signals share the same mechanism but use independent keys and different seeding windows over normalized text, making one resilient to edits and the other sensitive to reader-visible changes.
- Score: 68.64050157343334
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: Watermarking LLM-generated text is an important task for tracing its provenance. Existing LLM watermarks preserve provenance under editing, but this same robustness allows an adversary to alter critical content while retaining attribution, a vulnerability known as piggyback spoofing. We introduce an innovative watermark that jointly provides provenance and tamper evidence. It co-embeds a robust signal and a fragile signal into each generated token. The signals share the same mechanism but use independent keys and different seeding windows over normalized text, making one resilient to edits and the other sensitive to reader-visible changes. Multiple rounds of unbiased tournament reweighting preserve the expected generation distribution, while a periodic round-allocation pattern controls the trade-off between the two signals. At detection, their scores form a two-dimensional space supporting three decisions: Intact, Tampered, and No-Watermark. Across two large language models and two prompt datasets, our method demonstrates the highest tamper-detection rate among the evaluated methods while maintaining competitive attribution robustness and perplexity. Ablation studies show that reliable three-state detection requires a well-defined notion of intactness, co-embedding of the two signals, and complementary sensitivity to edits.
Related papers
- A Locally Tokenized Generative Model for Robust Time-Series Watermarking [12.477366787279747]
We show that existing detectors, which rely on globally coupled re-encoding, suffer from bidirectional drift of the null distribution under post-editing attacks.<n>We propose L-VQVAE, a generative model in which each discrete token is produced from a short contiguous window, and LVQMark, a watermarking method over this token space.
arXiv Detail & Related papers (2026-08-20T07:25:41Z) - Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings [2.992414059774663]
This work presents a semantic watermarking scheme for large language models (LLMs)<n> Dual-Embedding Watermarking (DEW) uses contextual and token-level embeddings to enhance robustness against paraphrasing and translation.
arXiv Detail & Related papers (2026-06-30T12:51:30Z) - SWAN: Semantic Watermarking with Abstract Meaning Representation [61.15962841972814]
SWAN (Semantic Watermarking with Abstract Meaning Representation) is a novel framework that embeds watermark signatures into the semantic structure of a sentence.<n>As the signature is encoded at the semantic structure level, any paraphrase that preserves meaning automatically preserves the signature.
arXiv Detail & Related papers (2026-05-05T21:13:30Z) - Authenticated Contradictions from Desynchronized Provenance and Watermarking [48.47756819432157]
This work formalizes and empirically demonstrates the $textitIntegrity Clash$, a condition in which a digital asset carries a cryptographically valid C2PA manifest asserting human authorship.<n>We propose a cross-layer audit protocol that jointly evaluates provenance metadata and watermark detection status, achieving 100% classification accuracy across 3,500 test images.
arXiv Detail & Related papers (2026-03-02T20:42:12Z) - MC$^2$Mark: Distortion-Free Multi-Bit Watermarking for Long Messages [62.982950935139534]
Multi-bit watermarking can embed identifiers into generated text, but existing methods struggle to keep both text quality and watermark strength while carrying long messages.<n>We propose MC$2$Mark, a distortion-free multi-bit watermarking framework for reliable embedding and decoding of long messages.
arXiv Detail & Related papers (2026-02-15T07:29:06Z) - MerkleSpeech: Public-Key Verifiable, Chunk-Localised Speech Provenance via Perceptual Fingerprints and Merkle Commitments [0.0]
We propose MerkleSpeech, a system for public-key verifiable, chunk-localised speech provenance.<n>The system computes perceptual fingerprints over short speech chunks, commits them in a Merkle tree whose root is signed with an issuer key.<n>We present experiments targeting very low false positive rates under resampling, bandpass filtering, and additive noise.
arXiv Detail & Related papers (2026-02-10T11:58:19Z) - An Ensemble Framework for Unbiased Language Model Watermarking [60.99969104552168]
We propose ENS, a novel ensemble framework that enhances the detectability and robustness of unbiased watermarks.<n>ENS sequentially composes multiple independent watermark instances, each governed by a distinct key, to amplify the watermark signal.<n> Empirical evaluations show that ENS substantially reduces the number of tokens needed for reliable detection and increases resistance to smoothing and paraphrasing attacks.
arXiv Detail & Related papers (2025-09-28T19:37:44Z) - A Nested Watermark for Large Language Models [6.702383792532788]
Large language models (LLMs) can be misused to generate fake news and misinformation.<n>We propose a novel nested watermarking scheme that embeds two distinct watermarks into the generated text.<n>Our method achieves high detection accuracy for both watermarks while maintaining the fluency and overall quality of the generated text.
arXiv Detail & Related papers (2025-06-18T05:49:05Z) - Towards Copyright Protection for Knowledge Bases of Retrieval-augmented Language Models via Reasoning [58.57194301645823]
Large language models (LLMs) are increasingly integrated into real-world personalized applications.<n>The valuable and often proprietary nature of the knowledge bases used in RAG introduces the risk of unauthorized usage by adversaries.<n>Existing methods that can be generalized as watermarking techniques to protect these knowledge bases typically involve poisoning or backdoor attacks.<n>We propose name for harmless' copyright protection of knowledge bases.
arXiv Detail & Related papers (2025-02-10T09:15:56Z) - Bileve: Securing Text Provenance in Large Language Models Against Spoofing with Bi-level Signature [39.973130114073605]
We introduce a bi-level signature scheme, Bileve, which embeds fine-grained signature bits for integrity checks.
Bileve can differentiate 5 scenarios during detection, reliably tracing text and regulating LLMs.
arXiv Detail & Related papers (2024-06-04T03:58:14Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.