CSCI 780 Data-driven Security and Privacy
CSCI 780 data-driven security and privacy studies the design and implementation of secure computer systems utilizing data-oriented security analysis. Lectures cover threat models, attacks that compromise security, and techniques for achieving security, based on recent data-driven security research papers. Topics include the elements of data process techniques (such as natural language processing, machine learning); The applications of data processing techniques to various security and privacy problems, and practical issues arising from them; Secure and privacy-preserving machine learning algorithms; Attacks on machine learning algorithms.
Course information |
Instructor: Xiaojing Liao (xiaojing@wm.edu) |
Time: Tuesday, Thursday 12:30-13:50 |
Place: McGlothlin-Street Hall 2 |
Office hours: Tuesday, Thursday 14:00-15:30 |
Class Schedule |
8/31 Course Overview slides/syllabus 9/5 A Tour of Machine Learning Algorithms slides/reading 9/7 Machine Learning for Security slides/reading 9/12 Privacy-preserving DL/Attack on ML slides/reading1/reading2 9/14 NLP for Security slides/reading1/reading2 9/19 NLP for Security 2 slides/reading 9/21 Cloud Security slides/reading1/reading2 9/26 Guest Talk (Dr. Dmitry Evtyushkin): Side Channel Attack reading 9/28 Mobile Security slides/reading1/reading2 10/3 Mobile Security 2 slides/reading1/reading2 10/5 Web Security slides/reading 10/10 Cybercrime slides/reading 10/12 Threat Intelligence slides/reading 10/17 No class (Fall break) 10/19 PC meeting 10/24 PC meeting 10/26 Paper presentation 10/31 No class (Travel to CCS) 11/2 No class (Travel to CCS) 11/7 Paper presentation 11/9 Paper presentation 11/14 Paper presentation 11/16 Paper presentation 11/21 Paper presentation 11/23 No class (Thanksgiving break) 11/28 Project presentation 11/30 Project presentation 12/5 Project presentation 12/7 Project presentation |
Prerequisites |
There is no specific prerequisite course for this research topic class, however, a good understanding of basic computer security concepts (CSCI 554 Computer and Network Security or equivalent), machine learning techniques and natural language processing techniques will be helpful. |
Textbook |
No textbook required: a fair number of research papers will be read. Below are two reference books: Hacking: The Art of Exploitation (2nd Edition) by Jon Erickson Security Engineering: A Guide to Building Dependable Distributed Systems (2nd Edition) by Ross J. Anderson |
Grading |
10% Class Participant 15% Paper review assignment 25% Paper presentation 50% Final project |