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

Hao Ren; Hongwei Li; Xiaohui Liang; Shibo He; Yuanshun Dai; Lian Zhao

doi:10.3390/s16091463

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

Sensors (Basel). 2016 Sep 10;16(9):1463. doi: 10.3390/s16091463.

Authors

Hao Ren¹, Hongwei Li^{2

3}, Xiaohui Liang⁴, Shibo He⁵, Yuanshun Dai⁶, Lian Zhao⁷

Affiliations

¹ School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China. jingsboy@126.com.
² School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China. hongweili@uestc.edu.cn.
³ State Key Laboratory of Information Security, Institute of Information Engineering, Chinese Academy of Sciences, Beijing 100093, China. hongweili@uestc.edu.cn.
⁴ Department of Computer Science, University of Massachusetts at Boston, MA 02125, USA. Xiaohui.Liang@umb.edu.
⁵ State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China. s18he@iipc.zju.edu.cn.
⁶ School of Computer Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China. uestcdaiys@gmail.com.
⁷ Department of Electrical and Computer Engineering, Ryerson University, Toronto, ON M5B 2K3, Canada. lzhao@ee.ryerson.ca.

Abstract

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.

Keywords: cloud-assisted WBANs; differential privacy; fault tolerance; health data; multifunctional aggregation; privacy-enhanced.

MeSH terms

Algorithms
Computer Communication Networks
Computer Security
Data Collection*
Medical Informatics*
Privacy*