Privacy Enhancing technology

LELEC2770  2018-2019  Louvain-la-Neuve

Privacy Enhancing technology
5.0 credits
30.0 h + 30.0 h
1q

Teacher(s)
Standaert François-Xavier ; Pereira Olivier (coordinator) ;
Language
Anglais
Prerequisites

Familiarity with the basic notions of cryptography is welcome

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

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 :

  • AA1.2, AA1.3,
  • AA2.2, AA2.3, AA2.5,
  • AA3.1,
  • AA5.1, AA5.3, AA5.4, AA5.6,
  • AA6.1, AA6.2, AA6.3

Specific learning outcomes of the course

  • At the end of this class, the student will be able to  :
  • Analyze the risks of attacks against correctness and privacy for a concrete system
  • Understand cryptographic and architectural tools allowing to mitigate privacy issues
  • Evaluate utility and privacy metrics for databases and distributed systems

The contribution of this Teaching Unit to the development and command of the skills and learning outcomes of the programme(s) can be accessed at the end of this sheet, in the section entitled “Programmes/courses offering this Teaching Unit”.

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.

Teaching methods

Lectures and exercise sessions.

 

Evaluation methods

The final examination is based on exercises, based on the learning outcomes listed above. The practical details are given on Moodle.

Bibliography

Slides and references available on Moodle.

Faculty or entity


Programmes / formations proposant cette unité d'enseignement (UE)

Program title
Sigle
Credits
Prerequisites
Aims
Master [120] in Computer Science and Engineering
5
-

Master [120] in Data Science Engineering
5
-

Master [120] in data Science: Information technology
5
-

Master [120] in Electrical Engineering
5
-

Master [120] in Mathematical Engineering
5
-

Master [120] in Computer Science
5
-