Privacy-Preserving Technologies / Személyes adatok védelme (VIHIAV35)

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).



Kiadott anyagok

Course materials

A kiadott anyagokat a Moodle rendszeren keresztül lehet letölteni.

The course materials can be downloaded from the Moodle sytem.



during the semester

The mid-term test is on the last lecture. The final grade consist of the points obtained for the test with the extra points from attending the lectures. Failed classroom tests can be retaken again on the supplement week.

Órák ideje és helye

Time and location of classes



  • Wednesdays, 12:15 - 14:00, QBF08


Megbeszélés szerint, az előadóval előre egyeztetett időpontban.

Office hours

Please contact the lecturer to schedule an appointment.



Date Topic Lecturer
Febr 14 Introduction and Motivation B. Pejo
Febr 21 Dark Patterns: Types, Countermeasures, and Cognitive Biases B. Pejo
Febr 28 Tracking: Profiling, Data Brokers, and Web Tracking B. Pejo
Marc 6 Legal background of Data Protection: GDPR B. Pejo
Marc 13 De-anonymization: Structured & Unstructured Data B. Pejo
Marc 20 Re-identification: Entropy, Database Reconstruction, Query Auditing B. Pejo
Marc 27 Machine Learning Privacy: Model Extraction & Inversion, Membership & Property Inferencene B. Pejo
Apr 3 Holiday -
Apr 10 Anonymization Primitives, K-Anonymity, Synthetic Data B. Pejo
Apr 17 Differential Privacy: Properties, Mechanisms, Sensitivity, Dimensions B. Pejo
Apr 24 Cryptography: Theory (HE/SMPC/OT/SS/PSI/PIR/ZKP) B. Pejo
May 1 Holiday
May 8 Cryptography: Applications (Secure Messaging / Steganography / Cryptocurrencies / E-Voting) B. Pejo
May 15 ZH B. Pejo