Sebastian Zimmeck (Wesleyan University), Rafael Goldstein (Wesleyan University), David Baraka (Wesleyan University)

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.

View More Papers

Screen Gleaning: Receiving and Interpreting Pixels by Eavesdropping on...

Zhuoran Liu, Léo Weissbart, Dirk Lauret (Radboud University)

Read More

“Lose Your Phone, Lose Your Identity”: Exploring Users’ Perceptions...

Michael Lutaaya, Hala Assal, Khadija Baig, Sana Maqsood, Sonia Chiasson (Carleton University)

Read More

Preventing and Detecting State Inference Attacks on Android

Andrea Possemato (IDEMIA and EURECOM), Dario Nisi (EURECOM), Yanick Fratantonio (EURECOM and Cisco Talos)

Read More

ROV++: Improved Deployable Defense against BGP Hijacking

Reynaldo Morillo (University of Connecticut), Justin Furuness (University of Connecticut), Cameron Morris (University of Connecticut), James Breslin (University of Connecticut), Amir Herzberg (University of Connecticut), Bing Wang (University of Connecticut)

Read More