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A Study on Broker-Assisted Blockchain Trust Chains for Provenance and Integrity Verification of Generative Media Using Watermarking, Semantic Fingerprinting, and C2PA

Year: 2026
Type: article
Abstract: The widespread availability of generative artificial intelligence has increased the volume of images and videos shared online, while making it difficult to verify origin and integrity after routine post-processing such as re-encoding, resizing, and transcoding. This research proposes a broker-assisted trust chain architecture that treats authenticity verification as an evidence registration and validation workflow rather than a single-signal decision. A trust chain broker seals submitted media by embedding a robust hidden watermark, deriving an embedding-based semantic fingerprint, and producing standardized provenance metadata, then stores the sealed media off-chain using content-addressed storage and anchors only compact evidence on an immutable ledger. The anchored evidence binds the content identifier of the sealed artifact with semantic and provenance hashes, timestamps, and the broker signature, while scalable candidate discovery is supported through an off-chain Facebook AI Similarity Search (FAISS)-based nearest-neighbor similarity index. We evaluate the retrieval stage on a COCO 2017 validation subset (N = 200) under representative post-processing transformations (JPEG compression, resizing, and center cropping), and observe near-perfect candidate identification performance with Recall@1 = 0.9988 and Recall@5/10 = 1.000. During verification, the broker retrieves candidates by embedding similarity, validates ledger inclusion and broker signatures, applies consistency checks across evidence fields, and issues an operational verdict with a signed verification report that is independently checkable. We also implement an EVM-based proof-of-concept for on-chain anchoring and report low ledger-side overhead for a representative registration transaction (gasUsed = 25,380) when recording fixed-size compact evidence fields. The proposed architecture does not prevent copying itself, but improves traceability and auditability under realistic transformation and redistribution conditions by combining watermarking, semantic association, provenance binding, and tamper-evident evidence anchoring within a clear service accountability boundary.
DOI: 10.3390/app16073391
Language: English
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W7147460381
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