Protecting Personal Privacy under the Environment of Big Data

DOI

10.2991/ammsa-18.2018.21How to use a DOI?

Keywords

risk degree; vickrey-clark-groves (VCG); membership function; privacy pricing model

Abstract

Personal privacy of citizens under the environment of big data is a hot spot of social concern. This paper focuses on the issue of the commercialization and sharing of personal data. A simple analytic hierarchy process is used to rationally divide the risk of privacy and build an evaluation system. The privacy equivalent model is then established through the construction of membership functions in fuzzy theory and service level of Vickrey-Clark-Groves (VCG). At last, based on the problem of liability commitment, corresponding recommendations are studied under the data leakage mechanism.

Copyright

© 2018, 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  - Dandan Dong
AU  - Xuejun Zhou
PY  - 2018/05
DA  - 2018/05
TI  - Protecting Personal Privacy under the Environment of Big Data
BT  - Proceedings of the 2018 2nd International Conference on Applied Mathematics, Modelling and Statistics Application (AMMSA 2018)
PB  - Atlantis Press
SP  - 96
EP  - 100
SN  - 1951-6851
UR  - https://doi.org/10.2991/ammsa-18.2018.21
DO  - 10.2991/ammsa-18.2018.21
ID  - Dong2018/05
ER  -