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Data Certification Strategies for Blockchain-based Traceability Systems

Giacomo Zonneveld, Giulia Rafaiani, Massimo Battaglioni, Marco Baldi

TL;DR

The paper tackles the challenge of certifying large, continuously generated data on a public blockchain. It compares a naive per-data hashing approach with a Merkle-tree based aggregation, develops practical Merkle-tree generation/proof extraction methods, and introduces a multi-level indexed Merkle tree to handle blockchain transaction failures efficiently. Through cost models and numerical results, the authors demonstrate that Merkle-tree based certification substantially reduces on-chain transactions for high-volume streams, while still enabling decentralized verification and data integrity. The proposed framework has practical implications for supply-chain traceability and attendance certification in public blockchains, and sets the stage for further security analyses and optimized decentralized authentication using robust Merkle-based structures.

Abstract

The use of blockchains for data certification and traceability is now well established in both the literature and practical applications. However, while blockchain-based certification of individual data is clear and straightforward, the use of blockchain to certify large amounts of data produced on a nearly continuous basis still poses some challenges. In such a case, in fact, it is first necessary to collect the data in an off-chain buffer, and then to organize it, e.g., via Merkle trees, in order to keep the size and quantity of certification data to be written to the blockchain small. In this paper, we consider a typical system for blockchain-based traceability of a production process, and propose and comparatively analyze some strategies for certifying the data of such a process on blockchain, while maintaining the possibility of verifying their certification in a decentralized way.

Data Certification Strategies for Blockchain-based Traceability Systems

TL;DR

The paper tackles the challenge of certifying large, continuously generated data on a public blockchain. It compares a naive per-data hashing approach with a Merkle-tree based aggregation, develops practical Merkle-tree generation/proof extraction methods, and introduces a multi-level indexed Merkle tree to handle blockchain transaction failures efficiently. Through cost models and numerical results, the authors demonstrate that Merkle-tree based certification substantially reduces on-chain transactions for high-volume streams, while still enabling decentralized verification and data integrity. The proposed framework has practical implications for supply-chain traceability and attendance certification in public blockchains, and sets the stage for further security analyses and optimized decentralized authentication using robust Merkle-based structures.

Abstract

The use of blockchains for data certification and traceability is now well established in both the literature and practical applications. However, while blockchain-based certification of individual data is clear and straightforward, the use of blockchain to certify large amounts of data produced on a nearly continuous basis still poses some challenges. In such a case, in fact, it is first necessary to collect the data in an off-chain buffer, and then to organize it, e.g., via Merkle trees, in order to keep the size and quantity of certification data to be written to the blockchain small. In this paper, we consider a typical system for blockchain-based traceability of a production process, and propose and comparatively analyze some strategies for certifying the data of such a process on blockchain, while maintaining the possibility of verifying their certification in a decentralized way.

Paper Structure

This paper contains 16 sections, 4 equations, 8 figures, 2 tables, 1 algorithm.

Table of Contents

  1. Introduction
  2. Our contribution
  3. Related works
  4. Paper outline
  5. System model and certification approaches
  6. First approach: Single data certification
  7. Second approach: Multiple data certification
  8. Comparison of the proposed approaches
  9. Merkle Tree Generation and Merkle proof extraction
  10. Nodes indexing when $N$ is a power of $2$
  11. Merkle Tree generation procedure
  12. Proof extraction
  13. Multi-level Indexed Merkle Tree
  14. Use case: Proof of Attendance
  15. Numerical results
  16. ...and 1 more sections

Figures (8)

  • Figure 1: Blockchain-based data certification system model.
  • Figure 2: Example of indexing of a Merkle Tree with 8 leaves.
  • Figure 3: Example of indexing of a Merkle Tree with 5 leaves.
  • Figure 4: Example of proof extraction of leaf with index 13. The indexes in red represent the nodes whose hash digests are collected to compose the Merkle proof.
  • Figure 5: Example of a multi-level Merkle tree obtained before attempting to forward the transaction for the third time. Each colored box represents a different indexed Merkle tree.
  • ...and 3 more figures