UWisconsin CS 763: Security and Privacy in Data Science (Previously CS 839: Topics in Security and Privacy)
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.

99 lines
4.6 KiB

Lectures will be loosely organized around three core modules: differential
privacy, adversarial machine learning, and applied cryptography. We will also
cover two advanced modules: algorithmic fairness, and PL and verification
techniques.
4 years ago
This is a graduate seminar, so not all lectures are set in stone and there is
4 years ago
considerable flexibility in the material. If you are interested in something not
4 years ago
covered in the syllabus, please let me know!
## Readings and Homework
4 years ago
**Paper discussions** are a core component of this course. You are expected to
read papers before lecture, attend lectures, and participate in discussions.
Before every paper presentation, students are expected to read the paper closely
and understand its significance, including (a) the main problem addressed by the
paper, (b) the primary contributions of the paper, and (c) how the authors solve
the problem in some technical detail.
The topics we will be reading and thinking about are from the recent research
4 years ago
literature---peer-reviewed and published, but not always completely refined.
Most research papers focus on a very narrow topic and are written for a very
specific technical audience. It also doesn't help that computer science
researchers are generally not the clearest writers, though there are certainly
exceptions. These
[notes](https://web.stanford.edu/class/ee384m/Handouts/HowtoReadPaper.pdf) by
Srinivasan Keshav may help you get more out of reading papers.
To help you prepare for the class discussions, I will also send out a few
4 years ago
questions at least 24 hours before every paper presentation. **Before** each
lecture, you should send me brief answers---a short email is fine, no more than
4 years ago
a few sentences per question. These questions will help you check that you have
understood the papers---they are not meant to be very difficult or
time-consuming and they will not be graded in detail.
## Course Materials
For differential privacy, we will use the textbook *Algorithmic Foundations of
Data Privacy* (AFDP) by Cynthia Dwork and Aaron Roth, available
[here](https://www.cis.upenn.edu/~aaroth/Papers/privacybook.pdf).
## Course Project
4 years ago
The other main component is the **course project**. You will work individually
or in pairs on a topic of your choice, producing a conference-style write-up and
presenting the project at the end of the semester. Successful projects may have
the potential to turn into an eventual research paper or survey. Details can be
4 years ago
found [here](assignments/project.md).
4 years ago
## Grading and Evaluation
Grades will be assigned as follows:
- **Discussions: 15%** (Pre-lecture questions and class participation)
- **Paper presentation: 25%**
- **Final project: 60%** (First and second milestones, and final writeup)
## Learning Outcomes
By the end of this course, you should be able to...
4 years ago
- Summarize the basic concepts in differential privacy, applied cryptography,
language-based security, and adversarial machine learning.
- Use standard 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. We will meet for two 75-minute class
periods each week over the fall semester, and you should expect to work on
course learning activities for about 3 hours out of classroom for every class
period.
4 years ago
## Academic Integrity
The final project may be done individually or in groups of two students.
Collaborative projects with people outside the class may be allowed, but please
4 years ago
check with me first.
4 years ago
## 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.