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JAIT 2026 Vol.17(6): 1211-1227
doi: 10.12720/jait.17.6.1211-1227

A Verifiable Credential Framework for Traceable and Scalable Data Sharing: Application to Product Carbon Footprint

Nobuaki Endoh
NTT Space Environment and Energy Laboratories, NTT, Inc., Tokyo, Japan
Email: nobuaki.endou@ntt.com

Manuscript received November 18, 2025; revised December 22, 2025; accepted March 25, 2026; published June 26, 2026.

Abstract—Verifiable Credentials (VCs) technology is gaining traction as a means of transmitting trustworthy credentials in the digital world. One is its leading use cases currently being explored is sharing Product Carbon Footprint (PCF) data among companies in a supply chain. Advancing the application of VCs is expected to reveal technical challenges and opportunities for improvement, thereby fostering further technological development. This paper proposes a new model to enable data to be securely and efficiently shared using VCs. In our model, we propose two schemes that are independent and combinable. The first scheme is to share data that includes a watermark in a verifiable form. This scheme’s main advantage is that it allows shared data to be tracked and revoked. The second scheme is to make data sharing scalable in a manner in which downstream-product companies can verify that the data was created by certified upstream-product companies. To assess feasibility, we design, implement, and evaluate our proposed system for sharing PCF data. The results show that the proposed model significantly enhances security and efficiency. The proposed schemes, inspired by the challenges in sharing PCF data, are designed with general applicability, enabling them to be adapted to a wide range of scenarios.
 
Keywords—security, verifiable credentials, sustainability

Cite: Nobuaki Endoh, "A Verifiable Credential Framework for Traceable and Scalable Data Sharing: Application to Product Carbon Footprint," Journal of Advances in Information Technology, Vol. 17, No. 6, pp. 1211-1227, 2026. doi: 10.12720/jait.17.6.1211-1227

Copyright © 2026 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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