The Study of Data Publishing Technology based on the Differential Privacy in Social Networks

DOI

10.2991/iceeecs-16.2016.105How to use a DOI?

Keywords

Privacy Preservation; Differential Privacy; Social Networks

Abstract

With the increasing prevalence of social network, research on privacy preserving data publishing in the social network has received substantial attention recently, and the recent emergence of differential privacy has shown great promise for rigorous prevention of information publishing. In this paper, we applied the differential privacy to protect the user information during the data publishing and provided a holistic solution for data publication. In addition, we also explored the influence caused by the query function sensitivity and the privacy preserving budget. The results show that the privacy protection degree increases with the increasing of the privacy preserving budget, while decreases with the increasing of the query function sensitivity.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Nan Ning
AU  - Changlun Zhang
AU  - Zhanyong Jin
AU  - Zhan Yu
PY  - 2016/12
DA  - 2016/12
TI  - The Study of Data Publishing Technology based on the Differential Privacy in Social Networks
BT  - Proceedings of the 2016 4th International Conference on Electrical & Electronics Engineering and Computer Science (ICEEECS 2016)
PB  - Atlantis Press
SP  - 515
EP  - 520
SN  - 2352-538X
UR  - https://doi.org/10.2991/iceeecs-16.2016.105
DO  - 10.2991/iceeecs-16.2016.105
ID  - Ning2016/12
ER  -