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GANs Based Density Distribution Privacy-Preservation on Mobility Data
Joint Authors
Source
Security and Communication Networks
Issue
Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-13, 13 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2018-12-02
Country of Publication
Egypt
No. of Pages
13
Main Subjects
Information Technology and Computer Science
Abstract EN
With the development of mobile devices and GPS, plenty of Location-based Services (LBSs) have emerged in these years.
LBSs can be applied in a variety of contexts, such as health, entertainment, and personal life.
The location based data that contains significant personal information is released for analysing and mining.
The privacy information of users can be attacked from the published data.
In this paper, we investigate the problem of privacy-preservation of density distribution on mobility data.
Different from adding noises into the original data for privacy protection, we devise the Generative Adversarial Networks (GANs) to train the generator and discriminator for generating the privacy-preserved data.
We conduct extensive experiments on two real world mobile datasets.
It is demonstrated that our method outperforms the differential privacy approach in both data utility and attack error.
American Psychological Association (APA)
Yin, Dan& Yang, Qing. 2018. GANs Based Density Distribution Privacy-Preservation on Mobility Data. Security and Communication Networks،Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1214520
Modern Language Association (MLA)
Yin, Dan& Yang, Qing. GANs Based Density Distribution Privacy-Preservation on Mobility Data. Security and Communication Networks No. 2018 (2018), pp.1-13.
https://search.emarefa.net/detail/BIM-1214520
American Medical Association (AMA)
Yin, Dan& Yang, Qing. GANs Based Density Distribution Privacy-Preservation on Mobility Data. Security and Communication Networks. 2018. Vol. 2018, no. 2018, pp.1-13.
https://search.emarefa.net/detail/BIM-1214520
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214520