- Legal context for privacy in Europe
- Fundamental privacy terminology and concepts
- A range of privacy-enhancing technologies (PETs)
FDD3344 Privacy- Enhancing Technologies 7.5 credits

Information per course offering
Course offerings are missing for current or upcoming semesters.
Course syllabus as PDF
Please note: all information from the Course syllabus is available on this page in an accessible format.
Course syllabus FDD3344 (Spring 2019–)Content and learning outcomes
Course contents
Intended learning outcomes
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 (PETs)
- 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 PETs in particular and
- incorporate existing PETs into their research or start developing new ones.
Literature and preparations
Specific prerequisites
This course is for PhD students in Computer Science or related subjects.
Literature
The reading list will be available on the course website and will be amended as the course proceeds.
Examination and completion
If the course is discontinued, students may request to be examined during the following two academic years.
Grading scale
Examination
- EXA1 - Examination, 7.5 credits, grading scale: P, F
Based on recommendation from KTH’s coordinator for disabilities, the examiner will decide how to adapt an examination for students with documented disability.
The examiner may apply another examination format when re-examining individual students.
Other requirements for final grade
The grading is pass/fail. To pass the course, the students successfully complete the following tasks.
Do assigned reading
Select a topic
Suggest a relevant reading list for the other participants
Present the selected topic
Lead a discussion on the selected topic
Hand in a written assignment
Participate in at least 80% of the meetings, preferably in person
Missed meetings can be made up by a written report on the meeting topics.
Examiner
Ethical approach
- All members of a group are responsible for the group's work.
- In any assessment, every student shall honestly disclose any help received and sources used.
- In an oral assessment, every student shall be able to present and answer questions about the entire assignment and solution.
Further information
Course room in Canvas
Offered by
Main field of study
Education cycle
Supplementary information
This course has been developed within SWITS, which is a network for security researchers in Sweden, mainly PhD students. Together with Simone Fischer-Hübner at Karlstad Unversity, we offer this PhD course on Privacy-Enhancing Technologies that can be attended by SWITS PhD students also from other locations in Sweden.
Examiners are:
Sonja Buchegger at KTH and Simone Fischer-Hübner at KAU.