{"title":"理解在线隐私——隐私可视化和隐私设计指南的系统回顾","authors":"Susanne Barth, D. Ionita, P. Hartel","doi":"10.1145/3502288","DOIUrl":null,"url":null,"abstract":"Privacy visualizations help users understand the privacy implications of using an online service. Privacy by Design guidelines provide generally accepted privacy standards for developers of online services. To obtain a comprehensive understanding of online privacy, we review established approaches, distill a unified list of 15 privacy attributes and rank them based on perceived importance by users and privacy experts. We then discuss similarities, explain notable differences, and examine trends in terms of the attributes covered. Finally, we show how our results provide a foundation for user-centric privacy visualizations, inspire best practices for developers, and give structure to privacy policies.","PeriodicalId":7000,"journal":{"name":"ACM Computing Surveys (CSUR)","volume":"75 1","pages":"1 - 37"},"PeriodicalIF":0.0000,"publicationDate":"2022-02-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"18","resultStr":"{\"title\":\"Understanding Online Privacy—A Systematic Review of Privacy Visualizations and Privacy by Design Guidelines\",\"authors\":\"Susanne Barth, D. Ionita, P. Hartel\",\"doi\":\"10.1145/3502288\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Privacy visualizations help users understand the privacy implications of using an online service. Privacy by Design guidelines provide generally accepted privacy standards for developers of online services. To obtain a comprehensive understanding of online privacy, we review established approaches, distill a unified list of 15 privacy attributes and rank them based on perceived importance by users and privacy experts. We then discuss similarities, explain notable differences, and examine trends in terms of the attributes covered. Finally, we show how our results provide a foundation for user-centric privacy visualizations, inspire best practices for developers, and give structure to privacy policies.\",\"PeriodicalId\":7000,\"journal\":{\"name\":\"ACM Computing Surveys (CSUR)\",\"volume\":\"75 1\",\"pages\":\"1 - 37\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-02-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"18\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"ACM Computing Surveys (CSUR)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3502288\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACM Computing Surveys (CSUR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3502288","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Understanding Online Privacy—A Systematic Review of Privacy Visualizations and Privacy by Design Guidelines
Privacy visualizations help users understand the privacy implications of using an online service. Privacy by Design guidelines provide generally accepted privacy standards for developers of online services. To obtain a comprehensive understanding of online privacy, we review established approaches, distill a unified list of 15 privacy attributes and rank them based on perceived importance by users and privacy experts. We then discuss similarities, explain notable differences, and examine trends in terms of the attributes covered. Finally, we show how our results provide a foundation for user-centric privacy visualizations, inspire best practices for developers, and give structure to privacy policies.
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