A Privacy-Preserving Approach for Joint Carbon Reduction and Emission Allowance Trading Based on Secure Multi-Party Computation
秘密計算に基づく共同炭素削減と排出権取引のプライバシー保護アプローチ (AI 翻訳)
Yun Liu, Fangxuan Pei, Ziyu Chen, Jizhong Zhu, Xin Shen
🤖 gxceed AI 要約
日本語
本論文は、中国の排出権取引市場（CEA, CCER）におけるデータセキュリティと柔軟性の課題を解決するため、秘密計算（SMPC）を用いたプライバシー保護型の共同炭素削減・排出権取引手法（JCREAT）を提案する。主双対勾配法とSMPCを組み合わせ、社会的余剰を最大化しつつ参加者のプライバシーを保護する。シミュレーションで、最適性とプライバシー保護の両立を実証。
English
This paper proposes a privacy-preserving joint carbon reduction and emission allowance trading (JCREAT) scheme that integrates secure multi-party computation (SMPC) with primal-dual gradient algorithm to address data security and inflexible offset mechanisms in Chinese carbon markets (CEA, CCER). The method clears trades optimally while protecting participant privacy, validated by simulations.
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
本論文は中国の炭素市場に焦点を当てるが、日本の排出権取引制度（J-Credit等）やSSBJ開示においても取引データの機密性は重要。プライバシー保護技術の応用は、日本のカーボン・クレジット市場における参加者拡大やデータ連携の信頼性向上に示唆を与える。
In the global GX context
This paper addresses key challenges in carbon markets—privacy and efficiency—by proposing a cryptographic approach. It is relevant to global carbon pricing mechanisms, especially as voluntary and compliance markets seek secure digital infrastructure. The integration of SMPC could inform TCFD/ISSB-aligned disclosure systems that require secure data sharing.
👥 読者別の含意
🔬研究者:This paper presents a novel combination of SMPC with carbon market clearing, offering a methodological contribution for privacy-preserving market design.
🏢実務担当者:Corporate sustainability teams can learn about secure technologies for carbon credit trading that protect sensitive emission data.
🏛政策担当者:Regulators designing digital carbon market platforms should consider SMPC-based approaches to enhance trust and participation while maintaining data privacy.
📄 Abstract（原文）
To achieve the net zero objective, the Chinese government has established various types of carbon markets including China Emission Allowance (CEA) and Chinese Certified Emission Reduction (CCER). However, current carbon market face challenges such as inflexible offset mechanism for CCER and transaction data security weaknesses which collectively hinder efficient resource allocation. To address these issues, this paper proposes a privacy-preserving approach for Joint Carbon Reduction and Emission Allowance Trading (JCREAT). The scheme integrates the secure multi-party computation (SMPC) protocol using secret sharing with the primal-dual gradient algorithm. Specifically, a joint trading model considering CCER offset cap is first developed to maximize social welfare. Subsequently, a privacy-preserving clearing method utilizing SMPC is proposed to address carbon market data security issue. The method employs the primal-dual gradient algorithm to solve the joint trading model and applies the SMPC protocol to transform plaintext computations into ciphertext computations, thereby enhancing trading security. Simulation results show that the proposed scheme not only achieves the optimality of market clearing outcomes, but also effectively protects the privacy of participants, thereby validating the feasibility of integrating privacy-preserving computation with carbon market mechanism.
🔗 Provenance — このレコードを発見したソース
- semanticscholar https://doi.org/10.1109/tia.2025.3634044first seen 2026-05-22 04:45:03 · last seen 2026-05-27 04:56:23
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