Verifiable Privacy-Preserving Multidimensional Data Aggregation in Smart Healthcare via Blockchain

Multidimensional data aggregation is increasingly important in practical applications. There are some challenges, such as the risk of privacy leaks, accurate assessment of communication costs, effective verification of aggregation results, and defense against malicious node attacks. In this paper, we design a secure and efficient framework for multi-dimensional health data aggregation and sharing. This framework innovatively integrates blockchain technology, fog computing, homomorphic encryption, Pedersen commitment, and the ECDSA signature algorithm. By implementing this solution, we not only protect the privacy of aggregated data but also guarantee data consistency and authentication for data providers. Furthermore, by leveraging the homomorphic properties of Pedersen commitments, we can also check the validity of the final aggregation results. Experimental validation has demonstrated the efficiency and feasibility of our approach, indicating it is a practical solution for multidimensional data aggregation.

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Publication Details

Published
2025-06-20
DOI
https://doi.org/10.1109/gbc60041.2025.11134476
Primary Topic
Blockchain Technology Applications and Security
Type
article
Field-Weighted Citation Impact
0.00

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article

Verifiable Privacy-Preserving Multidimensional Data Aggregation in Smart Healthcare via Blockchain

Hang Zhou, Yuhang Ma, Liang Zhang
Blockchain Technology Applications and Security
article

Verifiable Privacy-Preserving Multidimensional Data Aggregation in Smart Healthcare via Blockchain

Hang Zhou, Yuhang Ma, Liang Zhang
article en

Abstract

Multidimensional data aggregation is increasingly important in practical applications. There are some challenges, such as the risk of privacy leaks, accurate assessment of communication costs, effective verification of aggregation results, and defense against malicious node attacks. In this paper, we design a secure and efficient framework for multi-dimensional health data aggregation and sharing. This framework innovatively integrates blockchain technology, fog computing, homomorphic encryption, Pedersen commitment, and the ECDSA signature algorithm. By implementing this solution, we not only protect the privacy of aggregated data but also guarantee data consistency and authentication for data providers. Furthermore, by leveraging the homomorphic properties of Pedersen commitments, we can also check the validity of the final aggregation results. Experimental validation has demonstrated the efficiency and feasibility of our approach, indicating it is a practical solution for multidimensional data aggregation.

Hainan University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 66%
Blockchain Technology Applications and Security
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