BM-PDA: Blockchain Based Multifunctional Private-Preserving Data Aggregation for e-Health Systems
Chen Wang, Qian Yang, Jian Shen, Q. M. Jonathan Wu, Debiao He · IEEE Transactions on Dependable and Secure Computing · 2025
Secure aggregation of medical data enables detailed data analysis and informed medical decision-making in e-health systems, optimizing data resources utilization and enhancing service quality and decision accuracy. However, the collection of large volumes of medical data poses a significant risk of privacy leakage. Most existing privacy-preserving data aggregation schemes focus on additive aggregation of single or multi-dimensional data, which greatly limits their applicability. This article introduces a blockchain-based multifunctional data aggregation (BM-PDA) scheme for e-health systems. First, BM-PDA supports overall aggregation queries of data samples and can compute the maximum and minimum values within these samples. Second, it enables selective data aggregation queries based on various user attributes. Furthermore, analysis shows that integrating these two algorithms protects both user’s private data and attribute data. Performance evaluations indicate that the computational and communication costs are acceptable, demonstrating the scheme’s practical applicability.