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67924-01 - Lecture: Privacy-Preserving Methods for Data Science and Distributed Systems (6 CP)
| Semester | spring semester 2023 |
| Further events belonging to these CP |
67924-01 (Lecture) 67924-02 (Practical course) |
| 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 |