Collaborative Research: VINES: Track 1:Quantum-Ready and AI-Enabled by Design: Resilient and Deployable Next-Gen Cellular Networks

This collaborative project aims to improve the security and resilience of next-generation wireless networks by making them quantum-secure and artificial intelligence-enabled. These networks will connect phones, vehicles, hospitals, emergency responders, smart cities, and billions of everyday devices. As society becomes increasingly dependent on wireless connectivity, these systems must remain trustworthy even when attackers attempt to steal information, impersonate legitimate users, disrupt communications, or exploit artificial intelligence tools. The project develops new methods to protect wireless networks from emerging threats posed by future quantum computers, malicious network infrastructure, and attacks targeting artificial intelligence-driven network management. The broader impact of this project is to strengthen the national infrastructure that depends on mobile networks, including transportation, emergency response, health care, and public services. Open-source software, protocol implementations, formal models, datasets, and evaluation tools will be released to support and inform industrial adoption and standards development. Educational activities will introduce students to post-quantum security, cellular networking, artificial intelligence security, and privacy-preserving computation. Outreach efforts will engage undergraduate students, graduate students, educators, and pre-college learners through research experiences, cybersecurity programs, and community activities. These efforts will expand participation and prepare a future workforce capable of building resilient communication system. The project is organized around three connected research thrusts. The first thrust develops compact and private post-quantum cryptographic tools, including identity-based signatures, threshold signatures, and blind signature protocols for constrained wireless environments. The second thrust integrates these tools into secure cellular protocols for device bootstrapping, authentication and key agreement, application key management, and mobile virtual network operator settings. The third thrust develops trustworthy machine learning for next-generation networks, including federated learning-based intrusion detection, differentially private model coordination, and post-quantum integrity verification for model updates. A shared experimental platform supports implementation, formal analysis, and large-scale evaluation. 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.