CAREER: Towards Privacy-Preserving Wireless Communication: Fundamental Limits and Coding Schemes

Ever-growing cyber-attacks can lead to data breaches and exposure of private user data held by third parties, including companies, government entities, or medical institutions. A possible solution to such a risk is to implement privacy-preserving protocols between users and third parties that prevent any private information disclosure in the first place. For instance, a user could prove to a third party that she holds a valid password without revealing the password. While solutions for such privacy-preserving problems exist, such solutions are poorly adapted to the open-access, noisy, bandwidth-limited, and distributed nature of wireless networks. Resorting to privacy-preserving protocols unadapted to wireless communication networks may result in suboptimal/inefficient solutions or, even worse, compromise privacy. This project addresses this challenge with a novel framework for privacy-preserving communication specifically adapted to wireless networks. The anticipated benefits are stronger privacy guarantees, improved data rates, and improved scalability, compared to traditional approaches. The project integrates an educational component in the broad field of cybersecurity under the form of i) graduate student training, ii) project- and research-oriented undergraduate student education, and iii) outreach to K-12 students. This project aims to build a comprehensive framework that will enable the fundamental understanding and design of privacy-preserving wireless communication protocols. The construction of this framework is organized around three thrusts. In the first thrust, to improve data rates and scalability, the project investigates novel building blocks for privacy-preserving protocols that incorporate wireless communication constraints and enable multiuser communication protocols. In the second thrust, the project investigates solutions to make privacy-preserving protocols robust to adversarial behaviors. For instance, legitimate protocol users could exhibit malicious behaviors, or unauthorized network users could launch wireless-specific attacks, such as eavesdropping, jamming, or man-in-the-middle attacks. In the third thrust, the project explores the construction of low-complexity wireless protocols with information-theoretic privacy guarantees via novel coding techniques from coding theory, cryptography, and deep learning. 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.