Transparency in App Analytics: Analyzing the Collection of User Interaction Data

June 20, 2023 Β· Declared Dead Β· πŸ› Conference on Privacy, Security and Trust

πŸ‘» CAUSE OF DEATH: Ghosted
No code link whatsoever

"No code URL or promise found in abstract"

Evidence collected by the PWNC Scanner

Authors Feiyang Tang, Bjarte M. Østvold arXiv ID 2306.11447 Category cs.SE: Software Engineering Cross-listed cs.CR Citations 2 Venue Conference on Privacy, Security and Trust Last Checked 4 months ago
Abstract
The rise of mobile apps has brought greater convenience and many options for users. However, many apps use analytics services to collect a wide range of user interaction data, with privacy policies often failing to reveal the types of interaction data collected or the extent of the data collection practices. This lack of transparency potentially breaches data protection laws and also undermines user trust. We conducted an analysis of the top 20 analytic libraries for Android apps to identify common practices of interaction data collection and used this information to develop a standardized collection claim template for summarizing an app's data collection practices wrt. user interaction data. We selected the top 100 apps from popular categories on Google Play and used automatic static analysis to extract collection evidence from their data collection implementations. Our analysis found that a significant majority of these apps actively collected interaction data from UI types such as View (89%), Button (76%), and Textfield (63%), highlighting the pervasiveness of user interaction data collection. By comparing the collection evidence to the claims derived from privacy policy analysis, we manually fact-checked the completeness and accuracy of these claims for the top 10 apps. We found that, except for one app, they all failed to declare all types of interaction data they collect and did not specify some of the collection techniques used.
Community shame:
Not yet rated
Community Contributions

Found the code? Know the venue? Think something is wrong? Let us know!

πŸ“œ Similar Papers

In the same crypt β€” Software Engineering

Died the same way β€” πŸ‘» Ghosted