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Privacy-Enhanced and Multifunctional Health Data Aggregation under Differential Privacy Guarantees

机译:差异隐私保证下的隐私增强和多功能健康数据聚合

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摘要

With the rapid growth of the health data scale, the limited storage and computation resources of wireless body area sensor networks (WBANs) is becoming a barrier to their development. Therefore, outsourcing the encrypted health data to the cloud has been an appealing strategy. However, date aggregation will become difficult. Some recently-proposed schemes try to address this problem. However, there are still some functions and privacy issues that are not discussed. In this paper, we propose a privacy-enhanced and multifunctional health data aggregation scheme (PMHA-DP) under differential privacy. Specifically, we achieve a new aggregation function, weighted average (WAAS), and design a privacy-enhanced aggregation scheme (PAAS) to protect the aggregated data from cloud servers. Besides, a histogram aggregation scheme with high accuracy is proposed. PMHA-DP supports fault tolerance while preserving data privacy. The performance evaluation shows that the proposal leads to less communication overhead than the existing one.
机译:随着健康数据规模的快速增长,无线人体区域传感器网络(WBAN)有限的存储和计算资源正成为其发展的障碍。因此,将加密的健康数据外包到云中已成为一种有吸引力的策略。但是,日期汇总将变得困难。一些最近提出的方案试图解决这个问题。但是,仍然存在一些未讨论的功能和隐私问题。在本文中,我们提出了一种在差分隐私下的隐私增强型多功能健康数据聚合方案(PMHA-DP)。具体来说,我们实现了一种新的聚合功能,加权平均(WAAS),并设计了一种隐私增强的聚合方案(PAAS),以保护聚合数据免受云服务器的攻击。此外,提出了一种高精度的直方图聚合方案。 PMHA-DP支持容错,同时保留数据隐私。性能评估表明,与现有提案相比,该提案导致更少的通信开销。

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