2.8 KiB
Security and privacy are rapidly emerging as critical research areas in computer science and beyond. Vulnerabilities in software are found and exploited almost everyday, with grave consequences. Personal data today is aggregated at large scales, increasing the risk of privacy violations or breaches. Finally, machine-learning (ML) algorithms are seeing real-world applications in critical sectors (e.g., health care, automation, and finance), but their behavior in the presence of malicious adversaries is poorly understood.
This advanced topics class will cover recent techniques from the frontiers of security and privacy research. Topics will be drawn from the following broad areas, depending on student interest:
Differential Privacy
- Basic properties and examples
- Advanced mechanisms
- Local differential privacy
Adversarial Machine Learning
- Training-time attacks
- Test-time attacks
- Model-theft attacks
Cryptographic Techniques
- Zero-knowledge proofs
- Secure multi-party computation
- Verifiable computation
Learning Outcomes
By the end of this course, you should be able to...
- Summarize the basic concepts in differential privacy, applied cryptography, and adversarial machine learning.
- Use techniques from differential privacy to design privacy-preserving data analyses.
- Grasp the high-level concepts from research literature on the main course topics.
- Present and lead a discussion on recent research results.
- Carry out an in-depth exploration of one topic in the form of a self-directed research project.
Credit Information
This is a 3-credit graduate seminar. For the first 10 weeks of the fall semester, we will meet for three 75-minute class periods each week. You should expect to work on course learning activities for about 3 hours out of classroom for each hour of class.
Access and Accommodation
The University of Wisconsin-Madison supports the right of all enrolled students to a full and equal educational opportunity. The Americans with Disabilities Act (ADA), Wisconsin State Statute (36.12), and UW-Madison policy (Faculty Document 1071) require that students with disabilities be reasonably accommodated in instruction and campus life. Reasonable accommodations for students with disabilities is a shared faculty and student responsibility. Students are expected to inform me of their need for instructional accommodations by the end of the third week of the semester, or as soon as possible after a disability has been incurred or recognized. I will work either directly with you or in coordination with the McBurney Center to identify and provide reasonable instructional accommodations. Disability information, including instructional accommodations as part of a student’s educational record, is confidential and protected under FERPA.