Parallel-Chain Provenance with Structural Merge-Absence: A Cross-Domain Substrate for Multi-Authority Audit Trails
We present a data-structural substrate for tracking parallel independent assessments of the same external object such that (i) each authority's chain remains structurally non-fusible, (ii) cross-chain references can be expressed without content disclosure across authorities, and (iii) each chain's history is cryptographically verifiable. The substrate (provenance_engine_v2) provides identity-by-history at the primitive level: two records with identical fold-sequences are substrate-identical, while two records with diverging histories become substrate-distinct. We demonstrate applicability across eight independent domains - patent prosecution, verifiable credentials, software bill-of-materials, AI model lineage, NGS variant interpretation, psychiatric assessment, credit rating actions, and bank credit intelligence - yielding 1322 passing test cases across the eight wrapper implementations. Seven of the eight domains exhibit merge-absence: parallel records cannot be fused at the substrate level. The eighth domain introduces a novel confidentiality-preserving cross-reference primitive supporting existence queries across parallel chains without content disclosure. We position this work as defensive prior art for the broader pattern, established by Bitcoin OpenTimestamps anchors on 2026-05-11. Rev 1 revision notes (2026-05-11, repository working draft): Section 2 expanded with CRDT, transparency-log, secure-audit-log, database-provenance, named-graph, and privacy-preserving-record-linkage literature; archival "parallel provenance" terminology disambiguated (Hurley); §7.2 formal-verification roadmap made concrete (TLA+ specification for E8/E26/E19/§3.6/§5/F5); §7.3 cryptographic-enforcement roadmap made concrete (MPC, PSI/PSI-cardinality, ZK audit, TEE); narrower "combination" novelty wording added. No substrate code or test count changes. Rev 0 (DOI 10.5281/zenodo.20127705) remains the original prior-art record.
Authors
- Berkan Karakus (ORCID: https://orcid.org/0009-0004-0471-1069)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-05-11
- DOI
- https://doi.org/10.5281/zenodo.20130032
- Primary Topic
- Scientific Computing and Data Management
- Type
- preprint