We will study privacy in a few settings where rigorous definitions and enforcement mechanisms are being developed–statistical disclosure limitation, semantics and logical specification of privacy policies that constrain information flow and use, principled audit and accountability mechanisms for enforcing privacy policies, anonymous communication protocols.
Lecture and project-based
ISR and ECE MS/Ph.D. students
An undergraduate course equivalent to 15-251 or permission of instructor.
- Understand formal, quantitative techniques for measuring and evaluating the privacy of algorithms and computer systems
- Learn about different techniques for provably protecting the privacy of a dataset
- Learn how algorithms can exhibit bias against populations and individuals
- Understand common countermeasures for training fair algorithms, and when to use which countermeasure
Faculty and instructors who have taught this course in the past
Anupam Datta, Giulia Fanti, Steven Wu