Due to the COVID-19 crisis, the information below is subject to change,
in particular that concerning the teaching mode (presential, distance or in a comodal or hybrid format).
5 credits
30.0 h + 30.0 h
Q1
Teacher(s)
Pereira Olivier (coordinator); Standaert François-Xavier;
Language
English
Main themes
The exact course topics will change from year to year. Examples of relevant topics include techniques that make it possible to :
- compute on encrypted data;
- build a database that can be queried without the server knowing which parts of it are accessed;
- have anonymous communications;
- make digital cash;
- shuffle cards over the internet;
- organize an election in which the organizers can't cheat;
- have services with access control that keep users untraceable;
- understand attacks against privacy, including de-anoymization/re-identification attacks, profiling, data mining and side-channel attacks;
- identify privacy issues related to mass surveillance and solutions to prevent them.
Aims
At the end of this learning unit, the student is able to : | |
1 |
Based on the LO referential of the program « Master in Electrical Engineering », this course contributes to the development, acquisition, and evaluation of the following learnging outcomes :
|
Content
Various themes will be discussed each year.
These themes may include: secure two-party and multi-party protocols, oblivious memories, verifiable voting, crypto-currencies, verifiable computation, anonymous credentials, differential privacy and big data, post-Snowden cryptography.
These themes may include: secure two-party and multi-party protocols, oblivious memories, verifiable voting, crypto-currencies, verifiable computation, anonymous credentials, differential privacy and big data, post-Snowden cryptography.
Teaching methods
Due to the COVID-19 crisis, the information in this section is particularly likely to change.
Lectures and exercise sessions.Homeworks and mini-projects may be proposed during the semester.
Evaluation methods
Due to the COVID-19 crisis, the information in this section is particularly likely to change.
The final examination is based on exercises, based on the learning outcomes listed above.One of more mini-projects may be proposed during the semester and contribute to the final grade.
The practical details are given on Moodle.
Online resources
Teaching materials
- Slides and online references are available from Moodle.
Faculty or entity
ELEC
Programmes / formations proposant cette unité d'enseignement (UE)
Title of the programme
Sigle
Credits
Prerequisites
Aims
Master [120] in Computer Science and Engineering
Master [120] in Computer Science
Master [120] in Electrical Engineering
Master [120] in Mathematical Engineering
Master [120] in Data Science Engineering
Master [120] in Data Science: Information Technology