Channel Reciprocity Based Attack Detection for Securing UWB Ranging by Autoencoder

TL;DR

This paper introduces a low-complexity, channel reciprocity-based attack detection method for UWB ranging systems using autoencoders, effectively identifying Ghost Peak attacks with over 99% success in simulations and experiments.

Contribution

It proposes a novel autoencoder-based detection scheme leveraging channel reciprocity to enhance UWB security against Ghost Peak attacks.

Findings

Achieves over 99% attack detection success rate.

Demonstrates effectiveness through simulation and experimental validation.

Low implementation cost and high feasibility.

Abstract

A variety of ranging threats represented by Ghost Peak attack have raised concerns regarding the security performance of Ultra-Wide Band (UWB) systems with the finalization of the IEEE 802.15.4z standard. Based on channel reciprocity, this paper proposes a low complexity attack detection scheme that compares Channel Impulse Response (CIR) features of both ranging sides utilizing an autoencoder with the capability of data compression and feature extraction. Taking Ghost Peak attack as an example, this paper demonstrates the effectiveness, feasibility and generalizability of the proposed attack detection scheme through simulation and experimental validation. The proposed scheme achieves an attack detection success rate of over 99% and can be implemented in current systems at low cost.