Journal
28TH ANNUAL NETWORK AND DISTRIBUTED SYSTEM SECURITY SYMPOSIUM (NDSS 2021)
Volume -, Issue -, Pages -Publisher
INTERNET SOC
DOI: 10.14722/ndss.2021.24100
Keywords
-
Funding
- Wesleyan University, its Department of Mathematics & Computer Science
- Anil Fernando Endowment
Ask authors/readers for more resources
This study shows that privacy policies generated with popular policy generators may not accurately reflect apps' privacy practices. By combining questionnaire-based methods with code analysis, PrivacyFlash Pro was developed to identify apps' privacy practices reliably. The tool was tested with 40 iOS app developers, showing promising results in identifying privacy practices and usability.
Various privacy laws require mobile apps to have privacy policies. Questionnaire-based policy generators are intended to help developers with the task of policy creation. However, generated policies depend on the generators' designs as well as developers' abilities to correctly answer privacy questions on their apps. In this study we show that policies generated with popular policy generators are often not reflective of apps' privacy practices. We believe that policy generation can be improved by supplementing the questionnaire-based approach with code analysis. We design and implement PrivacyFlash Pro, a privacy policy generator for iOS apps that leverages static analysis. PrivacyFlash Pro identifies code signatures - composed of Plist permission strings, framework imports, class instantiations, authorization methods, and other evidence - that are mapped to privacy practices expressed in privacy policies. Resources from package managers are used to identify libraries. We tested PrivacyFlash Pro in a usability study with 40 iOS app developers and received promising results both in terms of reliably identifying apps' privacy practices as well as on its usability. We measured an F-1 score of 0.95 for identifying permission uses. 24 of 40 developers rated PrivacyFlash Pro with at least 9 points on a scale of 0 to 10 for a Net Promoter Score of 42.5. The mean System Usability Score of 83.4 is close to excellent. We provide PrivacyFlash Pro as an open source project to the iOS developer community. In principle, our approach is platform-agnostic and adaptable to the Android and web platforms as well. To increase privacy transparency and reduce compliance issues we make the case for privacy policies as software development artifacts. Privacy policy creation should become a native extension of the software development process and adhere to the mental model of software developers.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available