Dynamic Release of Big Location Data Based on Adaptive Sampling and Differential Privacy
Yan, Yan1,2; Zhang, Lianxiu1; Sheng, Quan Z.2; Wang, Bingqian1; Gao, Xin1; Cong, Yiming1
2019
Source PublicationIEEE ACCESS
ISSN2169-3536
Volume7Pages:164962-164974
AbstractData releasing is a key part bridging between the collection of big data and their applications. Traditional methods release the static version of dataset or publish the snapshot with a fixed sampling interval, which cannot meet the dynamic query requirements and query precision for big data. Moreover, the quality of published data cannot reflect the characteristics of the dynamic changes of big data, which often leads to subsequent data analysis and mining errors. This paper proposes an adaptive sampling mechanism and privacy protection method for the release of big location data. In order to reflect the dynamic change of data in time, we design an adaptive sampling mechanism based on the proportional-integral-derivative (PID) controller according to the temporal and spatial correlation of the location data. To ensure the privacy of published data, we propose a heuristic quad-tree partitioning method as well as a corresponding privacy budget allocation strategy. Experiments and analysis prove that the adaptive sampling mechanism proposed in this paper can effectively track the trend of dynamic changes of data, and the designed differential privacy method can improve the accuracy of counting query and enhance the availability of published data under the premise of certain privacy intensity. The proposed methods can also be readily extended to other areas of big data release applications.
KeywordBig location data privacy preserving data publishing adaptive sampling differentia privacy heuristic quad-tree partitioning
DOI10.1109/ACCESS.2019.2951364
Indexed BySCI
Language英语
Funding ProjectNational Nature Science Foundation of China[61762059][61762060][61862040]
WOS Research AreaComputer Science ; Engineering ; Telecommunications
WOS SubjectComputer Science, Information Systems ; Engineering, Electrical & Electronic ; Telecommunications
WOS IDWOS:000498712500001
PublisherIEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Document Type期刊论文
Identifierhttp://ir.lut.edu.cn/handle/2XXMBERH/76176
Collection计算机与通信学院
Corresponding AuthorYan, Yan
Affiliation1.Lanzhou Univ Technol, Sch Comp & Commun, Lanzhou 730050, Gansu, Peoples R China
2.Macquarie Univ, Fac Sci & Engn, Dept Comp, Sydney, NSW 2109, Australia
First Author AffilicationLanzhou University of Technology
Corresponding Author AffilicationLanzhou University of Technology
First Signature AffilicationLanzhou University of Technology
Recommended Citation
GB/T 7714
Yan, Yan,Zhang, Lianxiu,Sheng, Quan Z.,et al. Dynamic Release of Big Location Data Based on Adaptive Sampling and Differential Privacy[J]. IEEE ACCESS,2019,7:164962-164974.
APA Yan, Yan,Zhang, Lianxiu,Sheng, Quan Z.,Wang, Bingqian,Gao, Xin,&Cong, Yiming.(2019).Dynamic Release of Big Location Data Based on Adaptive Sampling and Differential Privacy.IEEE ACCESS,7,164962-164974.
MLA Yan, Yan,et al."Dynamic Release of Big Location Data Based on Adaptive Sampling and Differential Privacy".IEEE ACCESS 7(2019):164962-164974.
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