A fair multi-attribute data transaction mechanism supporting cross-chain

Abstract

Reliable storage and high-speed data networks enable individuals to access high-quality Internet of Things (IoT) data for scientific research through global transactions. Blockchain technology provides transparency for institutions to securely store and manage IoT data, while cross-chain transaction mechanisms facilitate the flow of IoT data. However, fairness issues may arise when it comes to cross-chain transactions of IoT data. This paper proposes a mechanism for multi-attribute data transactions to support cross-chain. The solution utilizes Vickrey-Clarke-Groves (VCG) auction, Paillier, Intel SGX, and other technologies to design a secure and equitable data seller selection scheme. The scheme ensures that the selection process for data sellers is both informed and private. Additionally, we generate a key pair for each attribute in the dataset to produce the corresponding attribute data signature. The dataset’s legitimacy is verified through batch verification to ensure that the data seller’s purchased attributes align with their requirements. The exchange of crypto assets and private keys between data sellers and buyers is designed to achieve fair payment. Our research suggests that the scheme meets the necessary security standards, and simulation results confirm its feasibility and effectiveness.

Publication DOI: https://doi.org/10.1016/j.iot.2024.101339
Divisions: College of Business and Social Sciences > Aston Business School > Operations & Information Management
College of Business and Social Sciences > Aston Business School
Funding Information: This work was supported by the National Natural Science Foundation of China (Nos. 62072092, 62072093, 62102075); the Natural Science Foundation of Hebei Province, China (No. F2020501013); the Fundamental Research Funds for the Central Universities, China
Additional Information: Copyright © 2024 The Author(s). Published by Elsevier B.V. This is an open access article under the CC BY license (https://creativecommons.org/licenses/by/4.0/)
Uncontrolled Keywords: Fairness,Data transaction,IoT data,Multi-attribute,Cross-chain
Publication ISSN: 2542-6605
Last Modified: 01 Oct 2024 17:04
Date Deposited: 28 Aug 2024 15:04
Full Text Link:
Related URLs: https://linking ... 542660524002804 (Publisher URL)
http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2024-12
Published Online Date: 2024-08-26
Accepted Date: 2024-08-21
Authors: Fan, Kuan
Zhou, Chaozhi
Lu, Ning
Shi, Wenbo
Chang, Victor (ORCID Profile 0000-0002-8012-5852)

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