HES: An Effective Homomorphic Encryption-Based Scheme for Data Quality Verification in Data Trading
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Researchers |
Huayou Si – Shichong Wang – Yun Zhao – Wei Chen – Neal N. Xiong – Yuanyuan Qi – Rami Yared– Mengyang Li |
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Published in |
IEEE INTERNET OF THINGS JOURNAL, volume 12, issue 16, pp. 33579 - 33591, August 2025. |
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Abstract |
The digital economy is one of the most dynamic, fastest growing, and impactful domains in modern economic development. To fully exploit the potential value of data as an economic resource, many governments have implemented policies to encourage and regulate data circulation and Trade. However, current mechanisms for data circulation and transactions lack an effective approach for assessing data quality. This deficiency leads to inefficient data utilization and hinders the realization of its full economic value. This article proposes a decentralized homomorphic encryption-based scheme (HES) for data quality verification in data transactions, leveraging blockchain and cryptographic techniques. The proposed method introduces a data provenance token, which represents the original data, and employs cryptographic techniques to implement a zeroknowledge verification mechanism. This mechanism enables the verification of both the content and quality of the data while preserving data privacy. Buyers can verify datasets without accessing specific content or involving third-party intermediaries. In this decentralized framework, buyers can independently verify whether a dataset meets their requirements based solely on its content and quality metrics. Experimental results demonstrate that this approach effectively resolves the challenge of establishing data quality consensus in decentralized scenarios, enabling swift agreement between buyers and sellers on data quality. By doing so, it facilitates the circulation and trading of data assets, unlocking their value, and promoting economic growth. The findings provide a reliable and privacy-preserving data quality consensus mechanism for data transactions participants. Keywords: Blockchain, data quality, homomorphic encryption, zero-knowledge verification. |
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Link to abstract |
