Efficient Verifiable Credential Aggregation With Blockchain Anchoring and zk-SNARKs

Traditional digital identity systems struggle with centralization, vulnerability to manipulation, and a lack of transparency. In distributed identity, different cryptographic methods are used for issuing credentials, that create challenges during presentation. It suffer from a fundamental interoperability barrier with heterogeneous digital-signature schemes, forcing each verifier either to implement every scheme or to trust a central translation gateway. We propose a signature-agnostic verification framework that eliminates this barrier. The core idea is to commit a salted root hash of credential claims to a distributed ledger and ensure the authenticity using a smart contract. A zero-knowledge proof (zk-SNARK) is used to prove a selected claim set without revealing actual information. The verification reduces to a single hash-consistency check, and the verifier never touches issuer-specific signatures. A pleasant side effect is that the same verifiable presentation (VP) can be reused across verifiers and sessions, since trust derives from the on-chain anchor rather than transient signatures. This research will advance the identification ecosystem, enabling applications such as eKYC across finance, healthcare, and other sectors. We implement our method on Ethereum Virtual Machine (EVM) using Groth16, benchmark gas cost, proof size, and latency, and show its feasibility and computational efficiency. The privacy and security analysis confirms that the proposed solution is resistant to various attacks.

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Publication Details

Journal
IEEE Access
Published
2025-01-01
DOI
https://doi.org/10.1109/access.2025.3627625
Primary Topic
Cryptography and Data Security
Type
article
Field-Weighted Citation Impact
0.00
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article

Efficient Verifiable Credential Aggregation With Blockchain Anchoring and zk-SNARKs

Tadashi Nakano, Thi Hong Tran, Kentaroh Toyoda, Istiaque Ahmed
IEEE Access
Cryptography and Data Security
article

Efficient Verifiable Credential Aggregation With Blockchain Anchoring and zk-SNARKs

Tadashi Nakano, Thi Hong Tran, Kentaroh Toyoda, Istiaque Ahmed
article en

Abstract

Traditional digital identity systems struggle with centralization, vulnerability to manipulation, and a lack of transparency. In distributed identity, different cryptographic methods are used for issuing credentials, that create challenges during presentation. It suffer from a fundamental interoperability barrier with heterogeneous digital-signature schemes, forcing each verifier either to implement every scheme or to trust a central translation gateway. We propose a signature-agnostic verification framework that eliminates this barrier. The core idea is to commit a salted root hash of credential claims to a distributed ledger and ensure the authenticity using a smart contract. A zero-knowledge proof (zk-SNARK) is used to prove a selected claim set without revealing actual information. The verification reduces to a single hash-consistency check, and the verifier never touches issuer-specific signatures. A pleasant side effect is that the same verifiable presentation (VP) can be reused across verifiers and sessions, since trust derives from the on-chain anchor rather than transient signatures. This research will advance the identification ecosystem, enabling applications such as eKYC across finance, healthcare, and other sectors. We implement our method on Ethereum Virtual Machine (EVM) using Groth16, benchmark gas cost, proof size, and latency, and show its feasibility and computational efficiency. The privacy and security analysis confirms that the proposed solution is resistant to various attacks.

IEEE AccessVol. 13
Agency for Science, Technology and Research (SG), Republic Polytechnic (SG), Institute of High Performance Computing (SG), Metropolitan University (VE)
Openalex Percentile: Top 83%
Cryptography and Data Security
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Efficient Verifiable Credential Aggregation With Blockchain Anchoring and zk-SNARKs — Tadashi Nakano, Thi Hong Tran, et al. · IEEE Access (2025) | TGRS Research Map | TGRS