Privacy Risk Analysis to Enable Informed Privacy Settings

被引：13
|
作者：
De, Sourya Joyee [1 ]
Le Metayer, Daniel
机构：
[1] INRIA, Lyon, France
来源：
2018 3RD IEEE EUROPEAN SYMPOSIUM ON SECURITY AND PRIVACY WORKSHOPS (EUROS&PW 2018) | 2018年
关键词：
privacy risk analysis; harm trees; privacy settings; quantified self; fitness tracking device;
D O I：
10.1109/EuroSPW.2018.00019
中图分类号：
TP301 [理论、方法];
学科分类号：
081202 ;
摘要：
The work described in this paper is a contribution to enhancing individual control over personal data which is promoted, inter alia, by the new EU General Data Protection Regulation. We propose a method to enable better informed choices of privacy settings. The method relies on a privacy risk analysis parameterized by privacy settings. The user can express his choices, visualize their impact on the privacy risks through a user-friendly interface and, if needed, decide to revise them to reduce risks to an acceptable level.
引用
收藏
页码：95 / 102
页数：8
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