Today's Web services–such as Google, Amazon, and Facebook–leverage user data for varied purposes, including personalizing recommendations, targeting advertisements, and adjusting prices. At present, users have little insight into how their data is being used. Hence, they cannot make informed choices about the services they choose.
To increase transparency, we developed XRay, a scalable personal data tracking system for the Web. XRay predicts which data in an arbitrary Web account (such as emails, searches, or viewed products) is being used to target which outputs (such as ads, recommended products, or prices).
This talk covers the following:
1. An overview of XRay architecture: how we make it service-agnostic, provide targeting correlation across users.
2. Some interesting findings my team revealed across popular services–Gmail, Google Search, Amazon, Youtube, etc.
3. Future goals in our research.
If you want to know more, visit: xray.cs.columbia.edu