面向用户数据共享决策与理解的有效差分隐私通信

Aiping Xiong, Tianhao Wang, Ninghui Li, S. Jha
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引用次数: 35

摘要

差分隐私通过干扰聚合层(DP)或个体层(LDP)上的数据来保护个人隐私。我们报告了四个在线人类受试者实验,调查了在健康应用程序数据收集设置中使用不同方法向外行人传达不同隐私技术的影响。实验1和实验2考察了在给定不同DP或LDP描述时,被试对低敏感和高敏感个人信息的披露决策。实验3和4揭示了参与者数据共享决策背后的原因,并检查了参与者对这些DP或LDP描述的主观和客观理解。当被展示的描述是解释DP或LDP技术的含义而不是定义/过程时,参与者表现出比DP更好的理解和更愿意与LDP分享信息,这表明他们对LDP比DP更强的隐私保障的理解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards Effective Differential Privacy Communication for Users’ Data Sharing Decision and Comprehension
Differential privacy protects an individual’s privacy by perturbing data on an aggregated level (DP) or individual level (LDP). We report four online human-subject experiments investigating the effects of using different approaches to communicate differential privacy techniques to laypersons in a health app data collection setting. Experiments 1 and 2 investigated participants’ data disclosure decisions for low-sensitive and high-sensitive personal information when given different DP or LDP descriptions. Experiments 3 and 4 uncovered reasons behind participants’ data sharing decisions, and examined participants’ subjective and objective comprehensions of these DP or LDP descriptions. When shown descriptions that explain the implications instead of the definition/processes of DP or LDP technique, participants demonstrated better comprehension and showed more willingness to share information with LDP than with DP, indicating their understanding of LDP’s stronger privacy guarantee compared with DP.
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