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, encrypted traffic, source/binary code, 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 and the lectures such as
slides, administrative information, and supplementary materials. Consequently, this page always under construction.
The aim is to deliver (mainly technical) knowledge required by the General European Data Protection Regulation (GDPR) from Data Protection Officers (DPOs).
1 db nagy ZH elégséges szintű teljesítése, ami az összesen kapható pontszám legalább 40%-ának az elérését jelenti. A félévközi jegy a nagy ZH osztályzata. A félév során lehetőséget adunk a nagyzárthelyi pótlására. A sikertelen pótzárthelyi egy alkalommal ismételten pótolható a pótlási héten.
Megbeszélés szerint, az előadóval előre egyeztetett időpontban.
Please contact the lecturer to schedule an appointment.
| Date | Topic | Lecturer | Slides |
|---|---|---|---|
| TBA | Introduction and Motivation | G. Acs | TBA |
| TBA | Legal background of Data Protection: GDPR | G. Acs | TBA |
| TBA | Cryptography: Homomorphic Encryption, Private Set Intersection, Secure Multiparty Computation | M. Horváth | TBA |
| TBA | Privacy-preserving communication 1: TOR and attacks on TOR | G. Acs | TBA |
| TBA | Privacy-preserving communication 2: Secure Messaging (Signal), Oblivious Transfer, Private Information Retrieval | G. Acs | TBA |
| TBA | Web Tracking and Anti-Tracking | G. Acs | TBA |
| TBA | Personal data leakage from relational data: Uniqueness, Attribute Inference, Linking | G. Acs | TBA |
| TBA | Personal data leakage from unstructured data: Detection with Machine Learning, Web page fingerprinting, Code stylometry | G. Acs | TBA |
| TBA | Personal data leakage from aggregate data: Query auditing, Location recovery from density, Membership attack | G. Acs | TBA |
| TBA | Data anonymization: K-anonymity, Differential Privacy, RAPPOR | G. Acs | TBA |
| TBA | Privacy in Machine Learning: Modell inversion, Membership attack, Fairness | G. Acs | TBA |
| TBA | Interdependent Privacy | G. Biczók | TBA |
| TBA | Psychological profiling and manipulation, Cognitive Security | G. Acs | TBA |
| TBA | Test (ZH) | G. Acs | TBA |