Authors
Welderufael B Tesfay, Peter Hofmann, Toru Nakamura, Shinsaku Kiyomoto, Jetzabel Serna
Publication date
2018/4/23
Book
Companion Proceedings of the The Web Conference 2018
Pages
163-166
Description
With the continuing growth of the Internet landscape, users share large amount of personal, sometimes, privacy sensitive data. When doing so, often, users have little or no clear knowledge about what service providers do with the trails of personal data they leave on the Internet. While regulations impose rather strict requirements that service providers should abide by, the defacto approach seems to be communicating data processing practices through privacy policies. However, privacy policies are long and complex for users to read and understand, thus failing their mere objective of informing users about the promised data processing behaviors of service providers. To address this pertinent issue, we propose a machine learning based approach to summarize the rather long privacy policy into short and condensed notes following a risk-based approach and using the European Union (EU) General Data Protection …
Total citations
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Scholar articles
WB Tesfay, P Hofmann, T Nakamura, S Kiyomoto… - Companion Proceedings of the The Web Conference …, 2018