{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T15:06:09Z","timestamp":1773414369122,"version":"3.50.1"},"reference-count":39,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T00:00:00Z","timestamp":1773360000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004329","name":"Slovenian Research And Innovation Agency","doi-asserted-by":"publisher","award":["P2-0425"],"award-info":[{"award-number":["P2-0425"]}],"id":[{"id":"10.13039\/501100004329","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>Integrating third-party Machine Learning (ML) models into industrial Operational Technology (OT) creates a procurement deadlock: operators cannot verify vendor performance claims without sharing representative evaluation data with vendors, while vendors refuse to reveal proprietary model weights before purchase, rendering traditional safeguards such as Non-Disclosure Agreements technically unenforceable. This paper introduces a framework combining Zero-Knowledge Proofs (ZKPs) with smart contracts to enable trust-minimized, cryptographically verifiable competitive model procurement in Industrial Cyber-Physical Systems (ICPS). Vendors cryptographically prove that their model outperforms a legacy baseline without disclosing proprietary weights, a process we term cryptographic performance attestation, while the on-chain workflow automates escrow, proof verification, and best-vendor selection with arbiter-based dispute resolution. ZKP privacy is scoped to vendor model weights; operator-side evaluation-data confidentiality is managed separately via synthetic, de-identified, or public benchmark data. We analyze three ZKP workflow variations and evaluate them on consumer-grade hardware, achieving proving times of approximately three seconds and sub-dollar on-chain verification costs under Layer-2 fee assumptions for the recommended single-proof variation, while identifying computational trade-offs of recursive proof aggregation. The entire verification phase operates offline with no impact on real-time OT control paths, bridging the IT\/OT pre-transaction trust gap while deferring artifact deployment to existing OT tooling.<\/jats:p>","DOI":"10.3390\/fi18030146","type":"journal-article","created":{"date-parts":[[2026,3,13]],"date-time":"2026-03-13T11:12:25Z","timestamp":1773400345000},"page":"146","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Model Procurement for Industrial Cyber-Physical Systems Using Cryptographic Performance Attestation"],"prefix":"10.3390","volume":"18","author":[{"given":"Jay","family":"Boji\u010d Burgos","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2836-5493","authenticated-orcid":false,"given":"Urban","family":"Sedlar","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1042-6203","authenticated-orcid":false,"given":"Matev\u017e","family":"Pusti\u0161ek","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering, University of Ljubljana, 1000 Ljubljana, Slovenia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2026,3,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Berardi, D., Callegati, F., Giovine, A., Melis, A., Prandini, M., and Rinieri, L. 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