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Privacy-Preserving Technologies

Személyes adatok védelme
A tantárgyleírás hatályossága
Hatályosság kezdete:
2026. March 21.
Hatályosság vége:
Subject name (Hungarian, English)
Személyes adatok védelme
Privacy-Preserving Technologies
Subject code BMEVIHIAV35
Subject type
Training Level
Course types and hours (weekly/semester)
Course type lecture tutorial laboratory
hours (weekly) 2 0 0
type (linked/independent)
Assessment type félévközi érdemjegy
Credits 2
Subject coordinator
Pejó Balázs
position: adjunktus
Responsible department
Hálózati Rendszerek és Szolgáltatások Tanszék
Faculty Villamosmérnöki és Informatikai Kar
Subject website
Primary curriculum type
Direct prerequisites – Strong prerequisite none
Direct prerequisites – Weak prerequisite none
Direct prerequisites – Parallel prerequisite none
Direct prerequisites – Milestone prerequisite none
Direct prerequisites – Exclusion none

Objectives

Programme
1. week: Introduction (Motivation, Highlights, Examples)
2. week: Dark Patterns (Types, Countermeasures, Cognitive Biases)
3. week: Tracking (Profiling, Data Brokers, Web Tracking, Fingerprinting)
4. week: Hidden Data (Sensitive information inference, data brokers, manipulation)
5. week: GDPR (Personal / Sensitive Data, Principles , Lawfulness of Data Processing)
6. week: Machine Learning (Inference / Reconstruction / Poisoning / Backdoors / Fairness)
7. week: ((Un)Structured) Data Deanonymization (Uniqueness, Inference, Fingerprinting)
8. week: (Aggregated) Data Deanonymization (Query Auditing, Location Reidentification)
9. week: Anonymization (Synthetic Data, K-Anonimity, Ad-hoc Methods)
10. week: Differential Privacy (Definitions, Properties, Sensitivity, Methods, Libraries)
11. week: Cryptography (Basics, HE, SMPC, OT, SS, PSI, PIR, ZKP, FE, PQC)
12. week: Cryptography (Secure Messaging, Mixnets, Tor, Cryptocurrencies, E-Voting)
13. week : Exam
14. week: Extra Class (Exam Retake / Repeat Cancelled Lecture)

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, machine learning models, etc.), and its detection as well as mitigations using Privacy Enhancing Technologies (PETS). The objective of the course is to provide skills needed by Data Protection Officers (DPO) and required by the European General Data Protection Regulation (GDPR). 

Learning outcomes

Ez a tantárgy a KKK rendeletben meghatározott, következő kompetenciák fejlesztését szolgálja:

Knowledge

No learning outcomes recorded.

Skills

No learning outcomes recorded.

Attitudes

No learning outcomes recorded.

Autonomy and responsibility

No learning outcomes recorded.

Oktatási módszertan

Lectures

Tanulástámogató anyagok

Online források
Course material (lecture notes) is available in; electronic format. Each lecture has separate references

Recommended preliminary knowledge for completing the subject

Knowledge type competencies
(azon előzetes ismeretek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Skill type competencies
(azon előzetes képességek és készségek összessége, amelyek megléte nem kötelező, de a tantárgy eredményes teljesítését nagyban elősegíti)
nincs
Recommended (non-compulsory) preliminary competencies
(azon ajánlott (nem kötelező) előzetesen megszerzendő kompetenciák összessége, amelyek jelentősen hozzájárulnak a tantárgy eredményes teljesítéséhez)
nincs
General rules
Requirements: Passing the mid-term exam requires achieving at least 50% of the total available points. The final semester grade is calculated based on the total score from the mid-term exam and any additional points earned during the semester. The extra points are 10% of the exam; they can be obtained via a homework. Without the extra points the best grade can also be achieved.  Additional possibilities: During the semester, there is an opportunity to retake the mid-term exams. An unsuccessful retake can be attempted once more during the supplementary week.
Assessment methods
In-term assessments

No detailed assessments provided.

Weight of in-term assessments

No weights provided.

Exam-period assessments

No detailed assessments provided.

Weight of exam elements

No weights provided.

Grade calculation

No grade thresholds provided.

Attendance requirements

No attendance requirements provided.

Rules for retake and resubmission

Not provided.

Short description

Not provided.

Detailed description

Not provided.

Recommended courses

Not provided.

Workload to complete the subject

No workload breakdown provided.

Validity of subject requirements
Requirements valid from:
Requirements valid until:
Curriculum placement

No curriculum placements recorded for this subject version.