HaloMark: A Spectral Threshold for Embedding-Vector Watermarking under C2PA
arXiv SecurityArchived Aug 11, 2026✓ Full text saved
arXiv:2608.08645v1 Announce Type: new Abstract: Foundation-model embeddings are now a primary data asset, but the content-provenance machinery built for images and audio does not transfer to them. C2PA binds to an asset with a stable bit-level or perceptual identity; embeddings have neither, since quantisation, projection, fine-tuning, and windowed averaging reshape them in normal use and break any fixed hash. We present HaloMark, a watermark for embedding vectors cryptographically bound to a C2
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Computer Science > Cryptography and Security
[Submitted on 9 Aug 2026]
HaloMark: A Spectral Threshold for Embedding-Vector Watermarking under C2PA
Tarun Sharma
Foundation-model embeddings are now a primary data asset, but the content-provenance machinery built for images and audio does not transfer to them. C2PA binds to an asset with a stable bit-level or perceptual identity; embeddings have neither, since quantisation, projection, fine-tuning, and windowed averaging reshape them in normal use and break any fixed hash.
We present HaloMark, a watermark for embedding vectors cryptographically bound to a C2PA manifest. It composes four standard primitives -- a block-diagonal orthogonal rotation, public whitening, an input-dependent LSH commitment, and a per-vector nonce -- around one protocol change: the producer signs the LSH commitment c into the C2PA sidecar, and the verifier reads c from the manifest instead of recomputing it. Recomputing is fragile under whitening, which flips the commitment bucket on 62% of inputs at cos = 0.96; reading the signed c reduces the verifier's score to T = T_null + beta(A)*epsilon, so security turns on a single scalar beta, which we bound rigorously for linear and non-adaptive attackers and characterise empirically for the adaptive case.
We evaluate against an adversary holding polynomially many clean/watermarked pairs under one key with full sidecar visibility, across eight baselines and ten adaptive attackers including denoising-autoencoder removal. The eleven encoders separate at an empirical threshold eff_rank(Sigma)/d ~= 0.19: above it, detection AUROC stays at 0.98 or higher across every in-budget attack on the three encoders we sweep in full, and at 0.965 or higher under single-seed DAE removal on the rest; below it every variant we tested fails. Why the threshold is dimension-uniform is left open. Deployed as a Qdrant admission filter, the verifier runs at 284 us and 24 bytes of sidecar per vector, validated end-to-end against three C2PA reference-SDK bindings.
Subjects: Cryptography and Security (cs.CR); Information Retrieval (cs.IR)
Cite as: arXiv:2608.08645 [cs.CR]
(or arXiv:2608.08645v1 [cs.CR] for this version)
https://doi.org/10.48550/arXiv.2608.08645
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Submission history
From: Tarun Kumar Sharma [view email]
[v1] Sun, 9 Aug 2026 11:36:59 UTC (117 KB)
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