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

Semester spring semester 2023
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: homomorphic encryption, secret sharing, secure multi-party computation
* Privacy preserving machine learning (DPSGD, PATE)
* Federated learning
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.
Weblink https://dmi.unibas.ch/de/studium/compute

 

Admission requirements Knowledge of the following topics is a plus, but not a prerequisite.
* Programming in Python
* Foundations of Distributed Systems (MA lecture offered in the fall semester)

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

Dates

Date Time Room
Monday 20.02.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 27.02.2023 16.15-18.00 Fasnachstferien
Monday 06.03.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 13.03.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 20.03.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 27.03.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 03.04.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 10.04.2023 16.15-18.00 Ostern
Monday 17.04.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 24.04.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 01.05.2023 16.15-18.00 Tag der Arbeit
Monday 08.05.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 15.05.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 22.05.2023 16.15-18.00 Spiegelgasse 1, Seminarraum 00.003
Monday 29.05.2023 16.15-18.00 Pfingstmontag
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)
Assessment format continuous assessment
Assessment details continuous assessment

Please note: 30% homework
40% project (writeup and presentation)
30% written exam

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

Expected date: 13 July 2023, 10-12 a.m., Spiegelgasse 1, room 00.003.
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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