Channel Reciprocity Based Attack Detection for Securing UWB Ranging by Autoencoder

TL;DR

The paper tackles distance-attacks on UWB ranging, notably Ghost Peak, by exploiting channel reciprocity to detect inconsistencies between the Channel Impulse Responses (CIR) observed at the two ranging ends. It introduces a low-complexity scheme that uses an autoencoder to extract compressed CIR features, which are compared across the Initiator and Responder after offline training, with quantization to minimize transmission overhead. The approach is validated through extensive simulations and practical experiments with a DW3110-based setup, achieving attack-detection probabilities exceeding 99% and very low false-alarm rates while preserving compatibility with IEEE 802.15.4z. The work offers a practical, scalable defense that enhances UWB ranging security without major changes to existing standards or deployments.

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.

Figures (6)

• Figure 1: The principle of DS-TWR and Ghost Peak attack
• Figure 2: Improved integrity check ranging model
• Figure 3: The structure of designed autoncoder
• Figure 4: Performance comparison for different parameters of autoencoder
• Figure 5: Performance of attack detection scheme proposed