| Book slides:
Slides roughly corresponding to the content of the book, and used in PhD and master courses.
- Introduction to the course
- Motivation, difficulties of the field, and terminology (Chapter 1). Definitions of anonymity set, disclosure (identity and attribute disclosure). Definition of the transparency principle. Privacy by design.
- Short summary of privacy models (Sec. 3.4). Among other privacy models, we mention the following ones: k-anonymity, reidentification, secure multiparty computation, differential privacy, integral privacy, homomorphic encryption.
- Privacy models and disclosure risk measures (content in Ch. 3 and Appendix A)
- Classification of data protection procedures (Sec. 3.5). Data protection procedures are classified according to (i) on whose privacy is being sought (i.e., respondent/data subject, holder/data controller, and user), (ii) our knowledge on the computations to be done (i.e., known/unknown), and (iii) the number of data sources (single, multiple).
- User privacy, some methods (Content in Chapter 4, includes PIR)
- Differential privacy and secure multiparty computation (Chapter 5)
- Masking methods (Chapter 6, part of Chapter 7)
- Result-driven approaches (Chapter 8.1) Methods to avoid disclosure of rules in rule mining.
- Tabular data protection (Chapter 8.2) Data protection mechanisms for tabular data.