Aiping Xiong, Chuhao Wu, Tianhao Wang, Robert W. Proctor, Jeremiah Blocki, Ninghui Li, Somesh Jha
{"title":"Exploring Use of Explanative Illustrations to Communicate Differential Privacy Models","authors":"Aiping Xiong, Chuhao Wu, Tianhao Wang, Robert W. Proctor, Jeremiah Blocki, Ninghui Li, Somesh Jha","doi":"10.1177/21695067231195006","DOIUrl":null,"url":null,"abstract":"Proper communication is key to the adoption and implementation of differential privacy (DP). In this work, we designed explanative illustrations of three DP models (Central DP, Local DP, Shuffler DP) to help laypeople conceptualize how random noise is added to protect individuals’ privacy and preserve group utility. Following a pilot survey and an interview, we conducted an online experiment ( N = 300) exploring participants’ comprehension, privacy and utility perception, and data-sharing decisions across the three DP models. We obtained empirical evidence showing participants’ acceptance of the Shuffler DP model for data privacy protection. We discuss the implications of our findings.","PeriodicalId":20673,"journal":{"name":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","volume":"42 37","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-12-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Human Factors and Ergonomics Society Annual Meeting","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1177/21695067231195006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Proper communication is key to the adoption and implementation of differential privacy (DP). In this work, we designed explanative illustrations of three DP models (Central DP, Local DP, Shuffler DP) to help laypeople conceptualize how random noise is added to protect individuals’ privacy and preserve group utility. Following a pilot survey and an interview, we conducted an online experiment ( N = 300) exploring participants’ comprehension, privacy and utility perception, and data-sharing decisions across the three DP models. We obtained empirical evidence showing participants’ acceptance of the Shuffler DP model for data privacy protection. We discuss the implications of our findings.