Information Privacy
A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory, Probability and Statistics".
Deadline for manuscript submissions: closed (30 June 2021) | Viewed by 2835
Special Issue Editor
Special Issue Information
Dear Colleagues,
Regardless of how secure an information transmission (or data sharing) scheme is, privacy is still a major concern in legal transactions of data, which is becoming more prominent with the advances in machine learning and data mining algorithms. This calls for strict regulations on data distribution, such as the general data protection regulation (GDPR) adopted by the European Union. However, many recent examples of de-anonymization attacks on publicly available anonymized data show that regulation alone will not be sufficient to limit access to private data. Therefore, a key open problem is how to satisfy sufficient privacy requirements while still enabling the benefits of data sharing, referred to as the utility–privacy trade-off. This calls for an interdisciplinary approach (from information theory, computer science, etc.) to develop privacy-preserving data disclosure techniques. In particular, investigating the connections between information-theoretic and data scientific privacy-preserving techniques is highly desirable.
Dr. Borzoo Rassouli
Guest Editor
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Keywords
- Information-theoretic privacy
- Data privacy
- Utility–privacy trade-off
- Inference attacks
- Privacy-preserving schemes
- Anonymization
- Differential privacy
- Private information
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