INFORMATION PRIVACY
INFORMATION PRIVACY
2025 Fall Term
Cyber Security 757
This course provides a comprehensive introduction to the fundamental concepts and techniques of differential privacy, a crucial framework for ensuring privacy protection in data analysis and sharing. Students will delve into the mathematical foundations of differential privacy, exploring notions of privacy loss, sensitivity, and noise injection, while gaining a solid understanding of how these concepts apply to a wide range of data-driven scenarios. Through a combination of theoretical lectures and practical hands-on exercises, students will learn how to design differentially private algorithms for tasks such as data aggregation, query answering, and machine learning.
Other Requirements: PREREQ: CYBER 701 OR ADMISSION TO COMPUTER SCIENCE GRADUATE PROGRAM
Class Schedule
Disclaimer
- This schedule is informational and does not guarantee availability for registration.
- Sections may be full or not open for registration. Please use WINS if you wish to register for a course.
| Section Details | Meeting Details & Topic | Instructor | Syllabus | ||
|---|---|---|---|---|---|
|
22-LEC 3821
3 Units
|
09/02 - 10/21 (8W1) |
Chandra Sharma
|
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| ONLINE | |||||
| Students must have access to the internet and an internet browser. A webcam may be required for remote exam monitoring. | |||||
