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67924-01 - Lecture: Privacy-Preserving Methods for Data Science and Distributed Systems (6 CP)

Semester spring semester 2025
Course frequency Irregular
Lecturers Isabel Wagner (isabel.wagner@unibas.ch, Assessor)
Content Data and systems based on data are of enormous value in our modern society: medical datasets can help develop new treatments; real-time location data can help optimize traffic flows or contain outbreaks in a pandemic; speech data can improve speech recognition systems for accessibility or convenience. However, data processing may violate the privacy rights of individuals. In this lecture, you will learn how data can be shared and analyzed in a privacy-preserving way.

The following topics will be covered:
1. Private data sharing
* Anonymization and de-anonymization attacks
* k-anonymity
* Differential privacy, local differential privacy
* Synthetic data generation
2. Private data analysis
* Cryptographic approaches: secret sharing, secure multi-party computation
* Privacy preserving machine learning (DPSGD, PATE)
* Federated learning
3. Censorship resistance
4. Privacy engineering
Learning objectives * Understand privacy risks in the contexts of distributed systems and data science
* Understand the principles behind different privacy-enhancing technologies and how they address the privacy risks
* Implement, configure, and evaluate privacy-preserving solutions
Bibliography Will be announced in the lecture.
Comments Note for students of the Master Data Science: you can take this lecture as part of the module "Systems Foundations".
Weblink https://dmi.unibas.ch/de/studium/compute

 

Admission requirements Foundations of Distributed Systems (offered in the fall semester) is a prerequisite. For students who have not taken it, the lecturer can provide the list of relevant topics for independent study.

Knowledge of the following topics is a plus, but not a prerequisite.
* Programming in Python

Students with reduced computer science background are encouraged to discuss their prior knowledge with the lecturer.
Language of instruction English
Use of digital media No specific media used

 

Interval Weekday Time Room
wöchentlich Monday 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
wöchentlich Friday 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003

Dates

Date Time Room
Monday 17.02.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 24.02.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 28.02.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 03.03.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 07.03.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 10.03.2025 16.15-18.00 Fasnachstferien
Friday 14.03.2025 12.15-14.00 Fasnachstferien
Monday 17.03.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 21.03.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 24.03.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 28.03.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 31.03.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 04.04.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 07.04.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 11.04.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 14.04.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 18.04.2025 12.15-14.00 Ostern
Monday 21.04.2025 16.15-18.00 Ostern
Friday 25.04.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 28.04.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 02.05.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 05.05.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 09.05.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 12.05.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 16.05.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 19.05.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 23.05.2025 12.15-14.00 Spiegelgasse 1, Seminarraum 00.003
Monday 26.05.2025 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Friday 30.05.2025 12.15-14.00 Auffahrt
Friday 20.06.2025 08.00-17.00 Biozentrum, Hörsaal U1.101
Thursday 10.07.2025 10.00-12.00 Biozentrum, Hörsaal U1.101
Modules Module: Applications of Distributed Systems (Master's Studies: Computer Science)
Module: Applications of Machine Intelligence (Master's Studies: Computer Science)
Module: Methods of Distributed Systems (Master's Studies: Computer Science)
Module: Systems Foundations (Master's Studies: Data Science)
Assessment format continuous assessment
Assessment details continuous assessment

Please note:
40% project (writeup and presentation)
60% written exam

A 50% score on homework sets is required to participate in the final exam.

Expected date: tba
Assessment registration/deregistration Reg.: course registration, dereg: cancel course registration
Repeat examination no repeat examination
Scale 1-6 0,5
Repeated registration as often as necessary
Responsible faculty Faculty of Science, studiendekanat-philnat@unibas.ch
Offered by Fachbereich Informatik

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