DocumentCode
3768791
Title
Efficient e-health data release with consistency guarantee under differential privacy
Author
Hongwei Li;Yuanshun Dai; Xiaodong Lin
Author_Institution
School of Computer Science and Engineering, University of Electronic Science and Technology of China, China
fYear
2015
Firstpage
602
Lastpage
608
Abstract
E-health data release, which answers the statistical queries of the Electronic Health Records (EHRs), has been widely adopted in modern health care services. However, since the EHRs contain sensitive information of the patients, the data release procedure may lead to the leakage of the privacy of patients if it is done without necessary protection measures in place. On addressing this, existing research literature introduces differential privacy to provide the necessary privacy guarantee. However, it is not suitable in sensitive e-health environments because it lacks the efficiency for data processing and updating. In this paper, we propose an efficient e-health data release scheme with consistency guarantee under differential privacy. Specifically, we improve the performance of the previous work by designing a new private partition algorithm of histogram and also proposing a heuristic hierarchical query method. We conduct real experiments and compare our scheme with the existing one to show that the proposal is more efficient in terms of data processing and updating. Moreover, we increase the accuracy of data release through consistency and give proof of privacy to show that the proposed algorithm is under ϵ-differential privacy.
Keywords
"Privacy","Histograms","Partitioning algorithms","Data privacy","Databases","Vegetation","Inference algorithms"
Publisher
ieee
Conference_Titel
E-health Networking, Application & Services (HealthCom), 2015 17th International Conference on
Type
conf
DOI
10.1109/HealthCom.2015.7454576
Filename
7454576
Link To Document