REU Site: CyberAI: Cybersecurity Solutions Leveraging Artificial Intelligence for Smart Systems
INSTITUTION
Tennessee Technological University, TN
PRINCIPAL INVESTIGATOR
Syed Rafay Hasan
FUNDING
$459K
YEAR
2024
MOONBASE SCORE
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Abstract
Tennessee Technological University will offer a renewed Research Experience for Undergraduates (REU) Site that will contribute to the security and privacy of various smart systems. The proposed REU site has a three-year plan to provide training to 30 undergraduate students in Research and Development (R&D) activities focused on cybersecurity solutions that leverage artificial intelligence (AI) for smart systems. Participants will gain knowledge in various areas, including cryptography, deep learning, federated and reinforcement learning, graph-based anomaly detection, and hardware attack countermeasures. Under the guidance of expert faculty mentors, students will learn how to define research problems, develop, implement, and evaluate solutions. In addition to enhancing the research experience for undergraduates, the site aims to (1) contribute to the cybersecurity workforce development, (2) increase the representation of female and minority students in cybersecurity, (3) encourage undergraduates to pursue graduate studies, (4) support TTU's focus on cybersecurity research, and (5) promote STEM enrollment. Inspired by recent advancements in AI, telecommunications (e.g., 5G cellular networks), sensing technologies, and computing, the concept of smart systems, such as smart power grids and smart healthcare, has emerged with the goal of enhancing our daily lives. These systems aim to revolutionize the services offered, but they also introduce security and privacy challenges. The proposed REU site will conduct research encompassing a wide range of attacks, including those targeting cyber/hardware vulnerabilities and security/privacy preservation. The site will employ an array of tools such as deep learning, federated learning, reinforcement learning, cryptography, and graph-based anomaly detection. The primary outcomes expected from this site's research efforts will include scholarly publications, machine learning models, simulations, instructional manuals, and more. By the end of the program, these students will possess valuable knowledge and skills, potentially igniting their interest in pursuing professional careers in the cybersecurity field. This is of paramount importance, given the existing shortage of cybersecurity professionals, and it aligns with the imperative of safeguarding our nation's security. 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.
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