In recent years, researchers have applied artificial intelligence (AI) to effectively solve important problems in cybersecurity. While significant research progress has been made in cybersecurity with the help of AI, there is a shortage of highly educated workers who can solve challenging problems at the intersection of AI and cybersecurity. This project will develop such a workforce by educating qualified individuals from diverse communities in cybersecurity and AI simultaneously. The project team will develop and deliver modular and project-based courses for graduate students that cover the basics of AI and cybersecurity using real-life problems. The development of innovative courses is intended to strengthen the student experience and to build a strong and diverse workforce in AI and cybersecurity that will fill the current voids in government, industry, and academia.

The project team will develop five modular courses for graduate students: (1) Scalable Advanced Analytics, (2) AI including Explainable Machine Learning (ML), (3) ML for Cybersecurity, (4) Cybersecurity for ML (e.g., Adversarial ML), and (5) Secure Blockchain Technologies. The design of these modular and hybrid courses will incorporate research-based pedagogies and innovative technologies. Courses will be offered in both instructor-led and student-directed learning formats to study the differences in learning outcome, if any, between these two different approaches. This project will provide important information regarding optimal methods to deliver interdisciplinary cybersecurity curricula and how the education community can effectively broaden access to cybersecurity education beyond typical classroom courses. The project team will conduct outreach activities to ensure participation by underrepresented populations and will disseminate findings through workshops at relevant meetings of professional societies.

This project is supported by a special initiative of the Secure and Trustworthy Cyberspace (SaTC) program to foster new, previously unexplored, collaborations between the fields of cybersecurity, artificial intelligence, and education. The SaTC program aligns with the Federal Cybersecurity Research and Development Strategic Plan and the National Privacy Research Strategy to protect and preserve the growing social and economic benefits of cyber systems while ensuring security and privacy.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Agency
National Science Foundation (NSF)
Institute
Division of Graduate Education (DGE)
Type
Standard Grant (Standard)
Application #
2039542
Program Officer
Li Yang
Project Start
Project End
Budget Start
2020-08-01
Budget End
2022-07-31
Support Year
Fiscal Year
2020
Total Cost
$239,855
Indirect Cost
Name
University of Texas at Dallas
Department
Type
DUNS #
City
Richardson
State
TX
Country
United States
Zip Code
75080