No lecture this week
Reminder: this week there will be no in person lecture. Recordings of the class will be available early next week. Good luck with finishing the first project!
Material from lectures and project registration
Welcome again to the PETS 2023 lecture. I've added the slides and recordings of yesterday's lecture to the materials section of the course. Slides for upcoming lectures will be available there as well in the future (and before the start of the... Read more
Welcome again to the PETS 2023 lecture. I've added the slides and recordings of yesterday's lecture to the materials section of the course. Slides for upcoming lectures will be available there as well in the future (and before the start of the lecture).
The programming projects for this course must be done in pairs. Please make sure to register your teams by Monday April 24 at the latest. You can create your team on your personal status page. If you have trouble finding a partner, feel free to use the Lab Assignment Forum to announce that you are looking.
Have a great weekend!
Digital technologies have become an essential part of our day to day live. While often beneficial, these technologies also bring great privacy risks. In this course you will learn how to mitigate these risks by design privacy-friendly systems and how to evaluate the privacy-protections offered by systems.
To reason about the privacy of systems you will learn how to define desirable privacy properties and how to reason about privacy attackers. Privacy can be violated both at the application level (i.e., what data parties exchange) as well as on the meta-data level (i.e., how parties exchange data). You will learn about techniques to offer protection at both of these layers.
On the application layer, we’ll discuss cryptographic techniques such as secure multi-party computation, homomorphic encryption and anonymous authentication that together can be used to ensure privacy at the application layer. We will also discuss data anonymisation techniques such as k-anonymity and differential privacy to enable privacy-friendly data publishing. On the meta-data level, we’ll explore techniques for anonymous communication, censorship resistance, (browser) tracking and location privacy.
At the end of this course you will be able to:
- Explain basic building-blocks for designing privacy-friendly systems
- Combine these building blocks to solve simple problems while maintaining privacy
- Evaluate the privacy of simple proposed systems.
The privacy-enhancing technologies class is an advanced lecture. You will learn a lot about how to design and analyse privacy-friendly systems, but this is not an easy 6EC course. A basic understanding of security and cryptography (as taught for example in CySec1/CySec2 or the Security course) is essential to be able to follow the material in this course. If you have not mastered this material we strongly recommend you to take this course next year instead.
Main Lecture: Thursdays from 2pm to 4pm
Exercises: Thursdays from 4pm to 5pm
Room: E9.1 (CISPA building), room 0.05 (main lecture room)
The following schedule is subject to small changes.
- April 13: Introduction to Privacy
- April 20: Secure Multi-Party Computation
- April 27: (Fully) Homomorphic Encryption
- May 4: Privacy-preserving authentication
- May 11: Anonymous communication
- May 18: no class (Ascension Day)
- May 25: Censorship resistance (recording or online)
- June 1: Tracking
- June 8: no class (Fronleichnam)
- June 15: Anonymization / protected data release
- June 22: Differential Privacy
- June 29: Location Privacy
The course will be fully in-person, and attending the lectures and exercise sessions is highly recommended. Attending online is not possible. As a courtesy, we will make a best effort attempt to publish recordings of the lectures. You should not assume that recordings will be available. We will not publish recordings of the exercise sessions.
Learning to reason about privacy is difficult. We strongly recommend that you attend the exercise sessions to practice your reasoning skills.
The final grade for this course consists of 60% for the final exam and 40% for the projects plus bonus points.
Grading subject to small changes. Details will be explained in the first lecture.
As part of this class you will work on two projects to implement and evaluate a privacy-preserving system. The projects are graded and must be completed in pairs (exceptions only possible after permission from the lecturer). The projects contribute 40% to the final grade: 15% for the first project and 25% for the second project. There is no option to improve the grade for the projects.
Midterm Exercise Set
There is a midterm exercises set. Possible grades are: Fail, Pass, Good (top 40%, 0.3pt bonus). A passing grade is required to be allowed to participate in the exam. If you receive a Fail (and only if you receive a Fail) you will have the opportunity to improve your submission.
Exam date: July 17, 6pm--8pm
Format: Written exam
Location: CISPA, E9 1, room 0.05
The final written exam tests your understanding of the material covered in the class, exercises and projects. You must receive a passing grade on the exam alone. If you do, the exam is graded and contributes 60% to the final grade. Having received a passing grade for the midterm exercise set is required to be allowed to participate in the exam.
Frequently Asked Questions
Can I still take this course if I took “Privacy Enhancing Technologies” (2021) before?
Yes. The Privacy Enhancing Technologies course of 2021 taught by Yang Zhang is very different from the current version of the course. You are therefore allowed to take both courses. However if you took the 2021 course, you must inform the lecturer as soon as possible. Failure to do so means we cannot award you a grade.