Understanding Privacy-Related Advice on Stack Overflow

Mohammad Tahaei, Tianshi Li, Kami Vaniea
{"title":"Understanding Privacy-Related Advice on Stack Overflow","authors":"Mohammad Tahaei, Tianshi Li, Kami Vaniea","doi":"10.2478/popets-2022-0038","DOIUrl":null,"url":null,"abstract":"Abstract Privacy tasks can be challenging for developers, resulting in privacy frameworks and guidelines from the research community which are designed to assist developers in considering privacy features and applying privacy enhancing technologies in early stages of software development. However, how developers engage with privacy design strategies is not yet well understood. In this work, we look at the types of privacy-related advice developers give each other and how that advice maps to Hoepman’s privacy design strategies. We qualitatively analyzed 119 privacy-related accepted answers on Stack Overflow from the past five years and extracted 148 pieces of advice from these answers. We find that the advice is mostly around compliance with regulations and ensuring confidentiality with a focus on the inform, hide, control, and minimize of the Hoepman’s privacy design strategies. Other strategies, abstract, separate, enforce, and demonstrate, are rarely advised. Answers often include links to official documentation and online articles, highlighting the value of both official documentation and other informal materials such as blog posts. We make recommendations for promoting the under-stated strategies through tools, and detail the importance of providing better developer support to handle third-party data practices.","PeriodicalId":74556,"journal":{"name":"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","volume":"2022 1","pages":"114 - 131"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"20","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings on Privacy Enhancing Technologies. Privacy Enhancing Technologies Symposium","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2478/popets-2022-0038","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 20

Abstract

Abstract Privacy tasks can be challenging for developers, resulting in privacy frameworks and guidelines from the research community which are designed to assist developers in considering privacy features and applying privacy enhancing technologies in early stages of software development. However, how developers engage with privacy design strategies is not yet well understood. In this work, we look at the types of privacy-related advice developers give each other and how that advice maps to Hoepman’s privacy design strategies. We qualitatively analyzed 119 privacy-related accepted answers on Stack Overflow from the past five years and extracted 148 pieces of advice from these answers. We find that the advice is mostly around compliance with regulations and ensuring confidentiality with a focus on the inform, hide, control, and minimize of the Hoepman’s privacy design strategies. Other strategies, abstract, separate, enforce, and demonstrate, are rarely advised. Answers often include links to official documentation and online articles, highlighting the value of both official documentation and other informal materials such as blog posts. We make recommendations for promoting the under-stated strategies through tools, and detail the importance of providing better developer support to handle third-party data practices.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
了解有关堆栈溢出的隐私相关建议
摘要隐私任务对开发人员来说可能具有挑战性,因此研究界制定了隐私框架和指南,旨在帮助开发人员在软件开发的早期阶段考虑隐私功能并应用隐私增强技术。然而,开发人员如何参与隐私设计策略尚不清楚。在这项工作中,我们研究了开发人员相互提供的与隐私相关的建议类型,以及这些建议如何与Hoepman的隐私设计策略相匹配。我们对过去五年中Stack Overflow上119个与隐私相关的公认答案进行了定性分析,并从这些答案中提取了148条建议。我们发现,建议主要围绕遵守法规和确保机密性,重点是告知、隐藏、控制和最小化Hoepman的隐私设计策略。其他策略,抽象的、分离的、强制执行的和演示的,很少被建议。答案通常包括官方文件和在线文章的链接,强调官方文件和其他非正式材料(如博客文章)的价值。我们提出了通过工具推广未充分说明的策略的建议,并详细说明了提供更好的开发人员支持以处理第三方数据实践的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
审稿时长
16 weeks
期刊最新文献
Editors' Introduction Compact and Divisible E-Cash with Threshold Issuance On the Robustness of Topics API to a Re-Identification Attack DP-SIPS: A simpler, more scalable mechanism for differentially private partition selection Privacy-Preserving Federated Recurrent Neural Networks
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1