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PrivacyGrade: Grading The Privacy Of Smartphone Apps

We're a team of researchers from Carnegie Mellon University. We have assigned privacy grades to Android apps based on some techniques we have developed to analyze to their privacy-related behaviors. Learn more here or browse our analyzed apps.

* Selected apps by us showcasing the full spectrum of grades
* The apps with the most user ratings in the Google Play Store

How Are Privacy Grades Assigned?

Grades are assigned using a privacy model that we built. This privacy model measures the gap between people's expectations of an app's behavior and the app's actual behavior. For example, according to studies we have conducted, most people don't expect games like Cut the Rope to use location data, but many of them actually do. This kind of surprise is represented in our privacy model as a penalty to an app’s overall privacy grade. In contrast, most people do expect apps like Google Maps to use location data. This lack of surprise is represented in our privacy model as a small or no penalty.

For more details see our Ubicomp 2012 and SOUPS 2014 research papers.

Our Work in the News

About Our Team

We are a team of researchers at Carnegie Mellon University, primarily part of the CHIMPS lab. The team is led by Professor Jason Hong.

The main work behind PrivacyGrade was done by Jialiu Lin, Shahriyar Amini, Song Luan, Kevin Ku, Mike Villena, Bharadwaj Ramachandran, and Richmond Wong. Professors Janne Lindqvist, Norman Sadeh, and Joy Zhang also helped with some of the ideas in PrivacyGrade.

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