What Makes a Good Exchange? Privacy-Preserving and Fair Contract Agreement in Data Trading

Exchange-assisted data trading (EADT) has become an essential paradigm in current data marketplaces. With data exchanges, sellers and buyers can trade data in an efficient and convenient way. However, existing EADT systems are vulnerable to privacy violations. Sensitive information about the data owned by sellers (manifested as attributes of the data) and the purchasing requirements of buyers (manifested as interests) are highly susceptible to leakage. On the one hand, buyers and sellers have direct access to the type of data supplied or desired before the data transaction is established. On the other hand, the information about transactions between the seller and buyer is transparent to the exchange, including the content of the transaction contract. In addition, the participants are likely to repudiate the content of previously accepted contracts or trigger a bidding war by contract first authorized by others, which raises threats towards authenticity and fairness. In this paper, we investigate the contract agreement in actual EADT systems, enumerate the inherent requirements of secrecy and fairness, and formally define them. Then we propose a privacy-preserving and fair contract agreement framework, dubbed PFCA, which consists of order-matching, negotiation, and authorization. We further propose a practical instantiation of PFCA, dubbed BestPFCA, utilizing efficient private set intersection (PSI), secure messaging (SM), and three-party signature (TPS). In addition, we also implement a BestPFCA prototype and conduct a comprehensive performance evaluation, which demonstrates the efficiency and practicality of BestPFCA.

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Publication Details

Journal
IEEE Transactions on Information Forensics and Security
Published
2025-01-01
DOI
https://doi.org/10.1109/tifs.2025.3558590
Citations
1
Primary Topic
Privacy, Security, and Data Protection
Type
article
Field-Weighted Citation Impact
4.20

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article

What Makes a Good Exchange? Privacy-Preserving and Fair Contract Agreement in Data Trading

Yaqing Song, Yuan Zhang, Weidong Qiu, Hongwei Li et al.
1 citations
IEEE Transactions on Information Forensics and Security
Privacy, Security, and Data Protection
4.20
article

What Makes a Good Exchange? Privacy-Preserving and Fair Contract Agreement in Data Trading

Yaqing Song, Yuan Zhang, Weidong Qiu, Hongwei Li, Xinyu He, Qiang Tang
article en
1 citations

Abstract

Exchange-assisted data trading (EADT) has become an essential paradigm in current data marketplaces. With data exchanges, sellers and buyers can trade data in an efficient and convenient way. However, existing EADT systems are vulnerable to privacy violations. Sensitive information about the data owned by sellers (manifested as attributes of the data) and the purchasing requirements of buyers (manifested as interests) are highly susceptible to leakage. On the one hand, buyers and sellers have direct access to the type of data supplied or desired before the data transaction is established. On the other hand, the information about transactions between the seller and buyer is transparent to the exchange, including the content of the transaction contract. In addition, the participants are likely to repudiate the content of previously accepted contracts or trigger a bidding war by contract first authorized by others, which raises threats towards authenticity and fairness. In this paper, we investigate the contract agreement in actual EADT systems, enumerate the inherent requirements of secrecy and fairness, and formally define them. Then we propose a privacy-preserving and fair contract agreement framework, dubbed PFCA, which consists of order-matching, negotiation, and authorization. We further propose a practical instantiation of PFCA, dubbed BestPFCA, utilizing efficient private set intersection (PSI), secure messaging (SM), and three-party signature (TPS). In addition, we also implement a BestPFCA prototype and conduct a comprehensive performance evaluation, which demonstrates the efficiency and practicality of BestPFCA.

IEEE Transactions on Information Forensics and SecurityVol. 20
The University of Sydney (AU), University of Electronic Science and Technology of China (CN), Shanghai Jiao Tong University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China
Openalex Percentile: Top 9%
Privacy, Security, and Data Protection
4.20
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