CRII: CIF: Exploiting, Modeling, and Leveraging Hidden Features in IoT for Efficient and Secure Communication
- Institution
- Texas Tech University, TX
- Principal investigator
- Wei Wang
- Funding
- $175K
- Duration
- 2025–2026
Moonbase score
Still being scored
Abstract
The number of Internet-of-Things (IoT) devices has been increasing exponentially. By connecting billions of IoT devices, they will be able to support diverse applications, such as healthcare, energy management, education, social interaction, and public safety. The advancement of these applications, however, hinges on the development of efficient and secure communication techniques to facilitate interactions with heterogeneous IoT devices. This project aims to introduce analysis, models, and techniques to foster seamless collaboration among heterogeneous IoT devices while ensuring their secure communication. The project should enrich the scientific knowledge of communication and security theory, signal processing, and networking. Furthermore, it has the potential to address the grand challenges in crowded wireless channels to support ubiquitous connectivity in heterogeneous IoT networks. Additionally, this project will contribute to the cross-disciplinary development of students at Saint Louis University and the establishment of graduate-level courses on IoT and communication theory. The objective of this project is to exploit, model, and leverage hidden features in heterogeneous IoT devices for cross-layer design, thereby improving the performance of IoT networks and enabling secure asymmetric communication across heterogeneous IoT devices with different communication protocols. The project is structured around two main thrusts. The first thrust introduces models and optimization techniques aimed at improving network performance across heterogeneous IoT devices by reducing latency and overhead, as well as enhancing throughput and reliability. The second thrust focuses on exploring and exploiting the unique and hidden physical-layer features of heterogeneous IoT devices, including spatial distribution of signal distortion and errors, to enable secure cross-IoT communication. 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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