Session 2: Mobile App Privacy Compliance

2:30 pm–3:45 pm

Abstract: 

Mobile apps are known to collect a wide variety of information about their users. Research has shown that many apps also fail to comply with basic privacy requirements (Federal, State or international). This session will provide an overview of techniques developed to automatically analyze mobile apps for potential privacy compliance violations. This will include an overview of natural language and machine learning techniques to analyze the text of privacy policies as well as static code analysis techniques to analyze what apps actually do. The tutorial will include a discussion of recent findings using this technology as well as a discussion of a mobile app privacy compliance tool to analyze mobile apps at scale. Participants will be given a chance to play with the tool and vet results it produces. This will include a discussion of possible uses for the tool in research, education, industry and regulatory contexts as well as opportunities for further extensions.

BibTeX
@conference {205185,
title = {Session 1: Semi-Automated Extraction of Data Practice Statements from Natural Language Privacy Policies},
year = {2017},
address = {Santa Clara, CA},
publisher = {{USENIX} Association},
month = jul,
}