グリーン人事管理におけるプライバシー保護型ESG報告のためのゼロ知識証明と許可型ブロックチェーン
Zero-Knowledge Proofs and Permissioned Blockchain for Privacy- Preserving ESG Reporting in Green Human Resource Management (原題)
Huynh Minh Sang
🤖 gxceed AI 要約
日本語
本論文は、ゼロ知識証明（Groth16 zk-SNARK）と許可型ブロックチェーンを組み合わせ、グリーン人事管理（GHRM）の個人データを秘匿したままESG開示用の集約クレームを監査可能にする枠組みを提案・評価する。Hyperledger Fabric上で実装し、証明生成は約1.2秒/1000件、検証は約8ms、バッチ処理でオンチェーン保存を92%削減、スループット210〜340TPSを達成した。準同型暗号や秘密計算との定性比較でプライバシーと監査性の両立が最も高いと評価された。
English
This paper proposes and evaluates a framework combining zero-knowledge proofs (Groth16 zk-SNARKs) with a permissioned blockchain to let auditors verify aggregate green HRM claims—such as training completion rates—without accessing individual employee data. Implemented on Hyperledger Fabric across two synthetic datasets and a 15,000-employee pilot, it achieved ~1.2s proof generation per 1,000 records, ~8ms verification, 92% on-chain storage reduction via Merkle batching, and 210–340 TPS. It was the only approach rated high on both privacy and auditability versus homomorphic encryption, MPC, and redacted ledgers.
Unofficial AI-generated summary based on the public title and abstract. Not an official translation.
📝 gxceed 編集解説 — Why this matters
日本のGX文脈において
SSBJ基準や有報での人的資本・サステナビリティ開示が拡大する中、従業員データの秘匿と監査可能性の両立は日本企業の実務課題。個人情報保護法制下でのESGデータ検証インフラ設計に示唆を与える。
In the global GX context
As ISSB/CSRD and SEC climate rules push assurance of workforce and social metrics, this work offers a cryptographic path to verifiable-yet-confidential disclosure—directly relevant to disclosure-infrastructure debates on auditability versus data protection.
👥 読者別の含意
🔬研究者:プライバシー保護と監査可能性を両立する暗号技術ベースのESG開示インフラの実装可能性と性能特性を評価できる。
🏢実務担当者:人的資本・GHRM指標を個人情報を開示せずに第三者保証へ供する際の技術的選択肢として検討できる。
🏛政策担当者:ESG開示における個人データ保護と検証可能性の両立に向けた制度設計の参考になる。
📄 Abstract（原文）
Green human resource management (GHRM) generates individual-level workforce data, such as environmental training records and employee contributions to carbon reduction, that organisations are increasingly expected to report under environmental, social and governance (ESG) disclosure rules, while data protection law requires these records to remain confidential. This study proposes and evaluates a framework that combines zero-knowledge proofs (ZKPs) with a permissioned blockchain to address this tension. Aggregate GHRM claims, for example that at least 80% of employees completed sustainability training, are proven with Groth16 zk-SNARKs over committed records, so that auditors can check a claim without access to individual data. A hybrid oracle network supplies threshold-signed commitments from the HR information system, Merkle-tree batching reduces on-chain storage, attribute-based access control limits detailed views to authorised roles, and threshold encryption protects off-chain records. The framework was implemented on Hyperledger Fabric and evaluated on two synthetic datasets (50,000 and 30,000 records) and in a pilot in an organisation of about 15,000 employees. Proof generation time increased approximately linearly (about 1.2 s per 1,000 records), verification took about 8 ms irrespective of input size, batching reduced on-chain storage by 92%, and throughput ranged from 210 to 340 transactions per second. In a qualitative comparison with homomorphic encryption, secure multi-party computation and a redacted ledger, the framework was the only approach rated high on both privacy and auditability. The findings suggest that verifiable, privacy-preserving workforce reporting is technically achievable, subject to trusted-setup and oracle assumptions and to further field testing.
🔗 Provenance — このレコードを発見したソース
- openalex https://doi.org/10.59324/ejtas.2026.4(5).47first seen 2026-11-03 04:48:34 · last seen 2026-11-06 04:44:55
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