Advancements in UWB: Paving the Way for Sovereign Data Networks in Healthcare Facilities

TL;DR

This paper explores the security and enhancement of UWB technology for healthcare, emphasizing device fingerprinting with deep learning and proposing a sovereign UWB network for secure localization and communication.

Contribution

It introduces novel deep learning-based device fingerprinting methods and discusses potential enhancements to UWB standards for establishing secure, sovereign data networks in healthcare.

Findings

Deep learning improves device fingerprinting accuracy.

UWB can enable secure localization in healthcare environments.

Proposed enhancements could establish sovereign UWB networks.

Abstract

Ultra-Wideband (UWB) technology re-emerges as a groundbreaking ranging technology with its precise micro-location capabilities and robustness. This paper highlights the security dimensions of UWB technology, focusing in particular on the intricacies of device fingerprinting for authentication, examined through the lens of state-of-the-art deep learning techniques. Furthermore, we explore various potential enhancements to the UWB standard that could realize a sovereign UWB data network. We argue that UWB data communication holds significant potential in healthcare and ultra-secure environments, where the use of the common unlicensed 2.4~GHz band-centric wireless technology is limited or prohibited. A sovereign UWB network could serve as an alternative, providing secure localization and short-range data communication in such environments.