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.

中文翻译：

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面向用户数据共享决策和理解的有效差异隐私通信

差分隐私通过在聚合级别 (DP) 或个人级别 (LDP) 上扰动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，研究了在健康应用程序数据收集设置中使用不同方法向非专业人士传达差异隐私技术的影响。实验 1 和实验 2 研究了在给定不同的 DP 或 LDP 描述时，参与者对低敏感和高敏感个人信息的数据披露决策。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。当显示解释含义的描述而不是 DP 或 LDP 技术的定义/过程时，