This course provides an introduction into the practical problems of data protection and privacy.
Students can develop skills of understanding and assessing privacy threats and designing
countermeasures. The course focuses on the problem of unwanted personal and sensitive data leakage from different information sources
(e.g., large datasets, web-tracking, machine learning models), and its detection as well as
mitigations using Privacy Enhancing Technologies (PETS). Rules and requirements are also available in Hungarian on the
official site of the course.
This page is the course homepage, which contains practical information related to the course such as administrative information and schedule.
Lecture slides and supplementary materials are available on Moodle.
The aim is to deliver (mainly technical) knowledge required by the General European Data Protection Regulation (GDPR) from Data Protection Officers (DPOs).
Attendance is mandatory (above 70% ~ 10 lecture). The mid-term test is on the last lecture, below the attendance limit it cannot be taken. The final grade consist of the points obtained for the test with the extra points for providing feedback about the classes during the semester. Failed classroom tests can be retaken again on the supplement week.
Megbeszélés szerint, az előadóval előre egyeztetett időpontban.
Please contact the lecturer to schedule an appointment.
Date | Topic | Lecturer | |
---|---|---|---|
Sept 6 | Introduction and Motivation | B. Pejo | |
Sept 13 | Dark Patterns: Types, Countermeasures, and Cognitive Biases | B. Pejo | |
Sept 20 | Tracking: Profiling, Data Brokers, and Web Tracking | B. Pejo | |
Sept 27 | Legal background of Data Protection: GDPR | B. Pejo | |
Oct 4 | Machine Learning Privacy: Model Extraction & Inversion, Membership & Property Inference, Reconstruction Attack, and Fairness | B. Pejo | |
Oct 11 | De-anonymization: Structured & Unstructured Data | B. Pejo | |
Oct 18 | Re-identification: Entropy, Database Reconstruction, Query Auditing | B. Pejo | |
Oct 25 | Anonymization Primitives, K-Anonymity, Synthetic Data | B. Pejo | |
Nov 1 | Holiday | ||
Nov 8 | Differential Privacy: Properties, Mechanisms, Sensitivity, Dimensions | B. Pejo | |
Oct 15 | Cryptography: Theory (HE/SMPC/OT/SS/PSI/PIR/ZKP) | B. Pejo | |
Oct 22 | Cryptography: Applications (Secure Messaging / Steganography / Cryptocurrencies / E-Voting) | B. Pejo | |
Oct 29 | Advanced Topic | B. Pejó | |
Dec 5 | Final test (ZH) | B. Pejo |