Is It a Trap? A Large-scale Empirical Study And Comprehensive Assessment of Online Automated Privacy Policy Generators for Mobile Apps
Shidong Pan, Dawen Zhang, Mark Staples, Zhenchang Xing, Jieshan Chen, Xiwei Xu, Thong Hoang
摘要
Privacy regulations protect and promote the privacy of individuals by requiring mobile apps to provide a privacy policy that explains what personal information is collected and how these apps process this information. However, developers often do not have sufficient legal knowledge to create such privacy policies. Online Automated Privacy Policy Generators (APPGs) can create privacy policies, but their quality and other characteristics can vary. In this paper, we conduct the first large-scale empirical study and comprehensive assessment of APPGs for mobile apps. Specifically, we scrutinize 10 APPGs on multiple dimensions. We further perform the market penetration analysis by collecting 46,472 Android app privacy policies from Google Play, discovering that nearly 20.1% of privacy policies could be generated by existing APPGs. Lastly, we point out that generated policies in our study do not fully comply with GDPR, CCPA, or LGPD. In summary, app developers must carefully select and use the appropriate APPGs with careful consideration to avoid potential pitfalls.
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引用它的顶会 Paper6
- Tinker, Tailor, Trust: How Developers Create Privacy Policies With and Without AIShiva Mayahi, Noura Alomar, Nathan MalkinCHI 2026 · 被引用 1 次
- A Big Step Forward? A User-Centric Examination of iOS App Privacy Report and EnhancementsLiu Wang, Dong Wang, Shidong Pan, Zheng Jiang 等S&P 2025
- I Can Tell Your Secrets: Inferring Privacy Attributes from Mini-app Interaction History in Super-appsYifeng Cai, Ziqi Zhang, Mengyu Yao, Junlin Liu 等USENIX Security 2025
- SKILLPoV: Towards Accessible and Effective Privacy Notice for Amazon Alexa SkillsJingwen Yan, Song Liao, Mohammed Aldeen, Luyi Xing 等NDSS 2025
- Evaluating Privacy Policies under Modern Privacy Laws At Scale: An LLM-Based Automated ApproachQinge Xie, Karthik Ramakrishnan, Frank LiUSENIX Security 2025
它引用的顶会 Paper10
- Privacy Policies over Time: Curation and Analysis of a Million-Document DatasetRyan Amos, Gunes Acar, Elena Lucherini, Mihir Kshirsagar 等WWW 2021 · 被引用 135 次
- The Rise of the Citizen Developer: Assessing the Security Impact of Online App GeneratorsMarten Oltrogge, Erik Derr, Christian Stransky, Yasemin Acar 等S&P 2018 · 被引用 69 次
- Have You been Properly Notified? Automatic Compliance Analysis of Privacy Policy Text with GDPR Article 13Shuang Liu, Baiyang Zhao, Renjie Guo, Guozhu Meng 等WWW 2021 · 被引用 68 次
- Understanding Challenges for Developers to Create Accurate Privacy Nutrition LabelsTianshi Li, Kayla Reiman, Yuvraj Agarwal, Lorrie Faith Cranor 等CHI 2022 · 被引用 56 次
- Consistency Analysis of Data-Usage Purposes in Mobile AppsDuc Bui, Yuan Yao, Kang G. Shin, Jong-Min Choi 等CCS 2021 · 被引用 41 次
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