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, 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.

Lecturers

Előadók

Célkitűzés

Objectives

The aim is to deliver (mainly technical) knowledge required by the General European Data Protection Regulation (GDPR) from Data Protection Officers (DPOs).

Követelmények

Requirements

A szorgalmi időszakban

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.

Órák ideje és helye

Time and location of classes

Előadás

Lecture

  • N/A, N/A

Konzultáció

Megbeszélés szerint, az előadóval előre egyeztetett időpontban.

Office hours

Please contact the lecturer to schedule an appointment.

Előadások

Lectures

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