Abstract
Show Abstract
Privacy policies are lengthy and hard to read, yet are profoundly important as they communicate the practices of an organization pertaining to user data privacy. Privacy Enhancing Technologies, or PETs, seek to inform users by summarizing these privacy policies. Efforts in the research and development of such PETs, however, have largely been limited to tools that recap the policy or visualize it. We present the next generation of our research and publicly available tool, PrivacyCheck v3, that utilizes machine learning to inform and empower users with respect to privacy policies. Privacy-Check v3 adds capabilities that are commonly absent from similar PETs. In particular, it adds the ability to (1) find the competitors of an organization with Alexa traffic analysis and compare policies across them, (2) follow privacy policies the user has agreed to and notify the user when policies change, (3) track policies over time and report how often policies change and their trends, (4) automat-ically find privacy policies in domains, and (5) provide a bird’s-eye view of privacy policies the user has agreed to. The new features of PrivacyCheck not only inform users about details of privacy policies, but also empower them to understand privacy policies at a higher level, make informed decisions, and even select competitors with better privacy policies.
Access Publication: Download PDF of Report
Downloads
/sites/default/files/2021-08/PrivacyCheck%20v3-%20Empowering%20Users%20with%20Higher-Level%20Understanding%20of%20Privacy%20Policies.pdf
Display Title