Privacy Enhancing Technologies (PET) PhD Course

Privacy has become an increasingly important topic as our data and data about us is both increasing and more and more being collected and mined. This course will give an overview of privacy concepts and terminology as well as concrete examples of privacy-enhancing technologies (PET) and some of their applications.

Course topics will include: Legal privacy basics, basic PET terms& concepts, anonymous communication (Mixes, Onion Routing, TOR, DC-Nets, etc.), data minimization technologies (blind signatures, zero-knowledge proofs, anonymous credentials, PIR, multi-party secure computation), Privacy policy languages (P3P, PPL, etc.), privacy-enhanced access control, transparency-enhancing tools, privacy-enhanced applications (privacy-enhanced identity management, PET for SNS, Cloud Computing, Smart Grids, eHealth systems etc.).

SWITS is a network for security researchers, primarily PhD students, in Sweden. This course on Privacy-Enhancing Technologies (PET) has been designed to accommodate SWITS PhD students from any location.

Objectives

The course objectives and learning outcomes are as follows.

Objectives

The students should be able to:

recognize threats to privacy
explain the basic privacy terminology and concepts and use them correctly
find and apply documentation of privacy-related problems and technologies
get an overview of existing privacy-enhancing technologies (PET)
analyze system PET descriptions in terms of their privacy protection and how they work
identify vulnerabilities of system descriptions and predict their corresponding threats
select counter-measures to identified threats and argue their effectiveness
compare counter-measures and evaluate their side-effects
present and explain their reasoning to others

such that the students can:

reason about privacy in general and PET in particular and
incorporate existing PET into their research or start developing new ones

Course Content

Legal context for privacy in Europe.
Fundamental privacy terminology and concepts.
A range of privacy-enhancing technologies (PET).

Prerequisites

This course is for PhD students in Computer Science or related subjects. There are no other special prerequisites.

Course responsible

The course is led jointly by Sonja Buchegger at KTH and Simone Fischer-Hübner at KAU. If you have any questions, please write to both buc at csc dot kth dot se and simone dot fischer-huebner at kau dot se.