Privacy Enhancing Technologies
Fall 2024
Instructor: Prof. Florian Tramèr
Contact: florian.tramer@inf.ethz.ch
Lectures: Monday 10:1512:00, HG E 7
Exercise Sessions: Tuesday 17:1518:00, CAB G 51 & CAB H 52, and Thursday 17:1518:00, CAB H 52 & NO C 44
Course catalog
Description
Privacy is a fundamental human right! And yet, technological advances (in particular in computer science) can often undermine privacy. In this class we will see how to formalize various notions of privacy and how to build systems that preserve privacy, by combining techniques from cryptography and statistics. The later parts of the course will focus on applications to machine learning.
Assignments
You must use LaTeX to write up your problem set. You must use the provided template to typset your assignment (the provided preamble can be handy for common notations).
You must submit your problem set via Gradescope. Please use the course code provided on Moodle to sign up. Note that Gradescope requires that the solution to each problem starts on a new page.
Please read the collaboration policy!You may discuss the problem sets with other students and you may work together to come up with solutions to the problems. If you do so, you must list the name of your collaborators on the first page of your submission. Each student must write up their problem set independently.
 Problem Set 1 (source, preamble) – due Friday, Oct 18 (out: Sep 23)
 Problem Set 2 – due Friday, Nov 8 (out: Oct 21)
 Problem Set 3 – due Friday, Nov 29 (out: Nov 11)
 Problem Set 4 – due Friday, Dec 20 (out: Dec 2)
Schedule
Date  Topic  Optional Readings 

Mo, Sep 23 


Mo, Sep 30 
 
Mo, Oct 7 


Mo, Oct 14 
 
Fr, Oct 18  Problem Set 1 Due at 11:59pm via Gradescope  
Mo, Oct 21 
 
Mo, Oct 28 


Mo, Nov 4 


Fr, Nov 8  Problem Set 2 Due at 11:59pm via Gradescope  
Mo, Nov 11 


Mo, Nov 18 


Mo, Nov 25 


Fr, Nov 29  Problem Set 3 Due at 11:59pm via Gradescope  
Mo, Dec 2 


Mo, Dec 9 


Mo, Dec 16 


Fr, Dec 20  Problem Set 4 Due at 11:59pm via Gradescope 
Feedback
This is the first time we teach this class, so we would love to get feedback on how to improve it! You can use this form to give us anonymous feedback throughout the semester. You can fill it out as often as you want. And we make mistakes! If something looks wrong or impossible, please let us know.
Course Staff
 Jie Zhang (Head TA)
 Laura Hetz (1st course half on crypto)
 Daniel Paleka (1st course half on crypto)
 Michael Aerni (2nd course half on DP)
 Hana Farid