Privacy Policy Analysis

Privacy-policy documents are a primary channel to inform users how their data is collected and/or shared, but they are hard for the users to understand due to their great length and use of legal/vague terms. Hard-to-understand privacy-policy documents can lead to blind consent or click-through agreements, placing users at privacy risks.

To alleviate the difficulties in reading/comprehending privacy policy documents, this project aims to analyze privacy policies and present them in an easy-to-read form to the users. Our approach includes analyzing privacy documents in a fine grain manner and designing user interfaces and models for improving user understanding of the documents. In particular, we create large annotated datasets of privacy policies and analyze them with neural natural language processing techniques.

Faculty

  • Kang G. Shin

Graduate Students

  • Duc Bui