Collaborative Research: SaTC: EDU: A Comprehensive Training Program of AI for 5G and NextG Wireless Network Security
- Institution
- University of South Florida, FL
- Principal investigator
- Zhuo Lu
- Funding
- $200K
- Duration
- 2023–2026
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Abstract
The emergence of 5G and next-generation (NextG) networks is transforming our lives into a new cyber era, featuring high connectivity and intensive data exchange. Such a highly connected world poses security and privacy challenges (e.g., how to safeguard sensitive data and ensure individual privacy). Traditional wireless network security designs may not adequately address these challenges, due to the complexity of handling a large amount of operational data. Recently, significant research efforts have been focused on adopting artificial intelligence (AI) techniques for 5G and NextG security because of their efficiency and capability of processing a variety of complex data to achieve intelligent functionalities. The future workforce needs comprehensive, coherent training in the intersection of 5G/NextG, security, and AI to gain a fundamental understanding of deploying AI techniques for wireless network security. This project aims to fill an essential educational gap between wireless network security and AI techniques by creating educational materials and training projects to train the future workforce in AI for 5G/NextG security. The project team will develop two major types of educational materials: (i) curriculum modules and (ii) project-based training. The lab-based curriculum modules for AI in 5G/NextG security will consist of three categories: physical layer, medium access control (MAC) and network layers, and network applications. In each module, state-of-the-art wireless equipment will be leveraged to create a real-world experiment-in-the-loop learning experience for students to observe and understand the advantages of AI for 5G/NextG security. Project-based training for students to will allow them to gain hands-on experience in developing and evaluating AI techniques to improve wireless network security. This project will enable various broader impacts, including undergraduate student training opportunities, openly disseminated training materials, and outreach activities. 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.
Research team
- Zhuo LuPI
- Yao Liu
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