I Read but Don't Agree
| Autor: | Welderufael B. Tesfay, Shinsaku Kiyomoto, Jetzabel M. Serna, Peter Hofmann, Toru Nakamura |
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| Rok vydání: | 2018 |
| Předmět: |
business.industry
Privacy policy 02 engineering and technology Benchmarking Service provider Machine learning computer.software_genre 020204 information systems General Data Protection Regulation 0202 electrical engineering electronic engineering information engineering Information disclosure media_common.cataloged_instance 020201 artificial intelligence & image processing The Internet Artificial intelligence European union business computer media_common |
| Zdroj: | WWW (Companion Volume) |
| DOI: | 10.1145/3184558.3186969 |
| Popis: | 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 Regulation (GDPR) aspects as assessment criteria. The results are promising and indicate that our tool can summarize lengthy privacy policies in a short period of time, thus supporting users to take informed decisions regarding their information disclosure behaviors. |
| Databáze: | OpenAIRE |
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