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ROI: A method for identifying organizations receiving personal data

arXiv 2204.09495 ↗First posted 19 Apr 2022cs.CR cs.LGcited by 0

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Abstract (arXiv)

Many studies have exposed the massive collection of personal data in the digital ecosystem through, for instance, websites, mobile apps, or smart devices. This fact goes unnoticed by most users, who are also unaware that the collectors are sharing their personal data with many different organizations around the globe. This paper assesses techniques available in the state of the art to identify the organizations receiving this personal data. Based on our findings, we propose ROI (Receiver Organization Identifier), a fully automated method that combines different techniques to achieve a 95.71% precision score in identifying an organization receiving personal data. We demonstrate our method in the wild by evaluating 10,000 Android apps and exposing the organizations that receive users' personal data.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 8 of its 48 references that are in the map. First posted on arXiv 19 Apr 2022.

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8 of 48 references.

References · 8

  1. 2018Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learningcited by 50
  2. 2015Automated Test Input Generation for Android: Are We There Yet?cited by 10
  3. 2021Are iPhones Really Better for Privacy? Comparative Study of iOS and Android Appscited by 6
  4. 2018Third Party Tracking in the Mobile Ecosystemcited by 5
  5. 2018An Automated Approach to Auditing Disclosure of Third-Party Data Collection in Website Privacy Policiescited by 5
  6. 2015Haystack: A Multi-Purpose Mobile Vantage Point in User Spacecited by 3
  7. 2020On the (Un)Reliability of Privacy Policies in Android Appscited by 2
  8. 2018Measuring third party tracker power across web and mobilecited by 1

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