Privacy-Preserving Digital Product Passports for Container Logistics: Design, Implementation and Experimental Evaluation of a oneM2M, EPCIS 2.0 and IOTA Platform with Zero-Knowledge Proofs

Abstract

Maritime shipping carries over 80% of global trade, yet cold-chain compliance verification forces a choice between disclosing sensitive telemetry and issuing unverifiable declarations. The EU's Digital Product Passport mandate requires verifiable provenance, but maritime IT systems lack a harmonized event model for interoperability. This thesis presents Ocean DPP, integrating EPCIS 2.0, oneM2M, IOTA anchoring, and Groth16 zero-knowledge proofs to verify compliance without revealing sensor data. Merkle-tree batching amortises on-chain cost, and sixteen experiments over 10,000+ events confirm 48 ms baseline latency, sub-10 ms proof verification, 37% scaling improvement, and zero message loss. The results demonstrate that privacy-preserving, standards-compliant DPPs are viable for maritime supply chains.