NSF Convergence Accelerator Track G: Secure Texting over Non-cooperative Networks and Anti-jamming Enhancement in 5G

With 5G cellular networks being progressively deployed worldwide, ensuring secure operation through 5G infrastructure is essential for the vast array of applications across military, government, and private sectors. Convergence research and development are required to accelerate the transformation of technical innovations into viable 5G domain products.

To address the multidisciplinary challenges in convergence research for securely operating through 5G infrastructure, George Mason University is partnering with Ericsson, AT&T, Michigan State University, and Morgan State University. Together we intend to solve comprehensive technical and socio-economic challenges, to achieve accelerated convergence.

For this Phase I project, the team proposes three research thrusts that will coherently address technical, economic, and policy challenges: 1) secure texting through non-cooperative cellular networks, 2) enhanced anti-jamming capabilities for cooperative 5G networks, and 3) socio-economic impact analysis of the proposed techniques. The anticipated communication security and resiliency enhancements are essential for military, government, and critical infrastructure applications, where stringent information privacy and availability are required.

Using critical infrastructure modeling and simulation techniques, these technical solutions will then be assessed in terms of their broader socio-economic impacts across a variety of use cases for different 5G vertical sectors. The decision support analytics produced will first help government and service providers prioritize which techniques should receive enhanced resources, and secondly encourage vendors, operators, and standards bodies to adopt and distribute these new security features based on benefit-cost merits.

Broadening participation activities will target women and African-American students by stimulating their interest in engineering, computer science, wireless technologies, cybersecurity, and artificial intelligence, through a number of educational and outreach programs. Outcomes from this project will be disseminated widely through data publishing, tutorials, publications, and software toolkits.

The proposed secure texting solution adds intelligence and adaptability to text devices that must covertly operate over untrusted radio networks including 5G. Combinations of coordination, natural language processing (NLP), encoding, translation, multiplexing and retransmission techniques are used to camouflage and harden secure text messages amongst consumer messages spread over multiple untrusted wireless networks.

This solution shall improve the privacy and reliability of sensitive text messaging over untrusted network environments where other brute force approaches are not possible. It is backward compatible with older generations of cellular networks. 5G spatial, time and frequency diversity mechanisms will be utilized and customized to enhance low-probability of detection/intercept (LPD/LPI) and anti-jamming capabilities of cooperative 5G networks, including randomized dynamic resource allocation, diversified beam switching, and multiple Transmission and Reception Point (mTRP)-based resilient communication.

Using infrastructure modeling and simulation techniques, the socio-economic implications of the proposed solutions will be assessed. The results produced by this analysis will be presented in terms of the potential direct and indirect economic impacts for a business-as-usual baseline (with no 5G security improvements), versus a strategy of enhanced 5G wireless security implemented using the techniques developed in this project.

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.