Reconstructing Robot Operations via Radio-Frequency Side-Channel

TL;DR

This paper demonstrates that passive radio-frequency side-channel analysis can accurately fingerprint robot movements and workflows, revealing operational details with high precision, thus exposing potential security vulnerabilities in teleoperated robotic systems.

Contribution

It introduces a novel passive attack method using RF side-channel analysis to reconstruct robot operations and workflows.

Findings

Fingerprinting robot movements with at least 96% accuracy

Near-perfect accuracy in reconstructing entire warehousing workflows

Highlights security risks in teleoperated robotic systems

Abstract

Connected teleoperated robotic systems play a key role in ensuring operational workflows are carried out with high levels of accuracy and low margins of error. In recent years, a variety of attacks have been proposed that actively target the robot itself from the cyber domain. However, little attention has been paid to the capabilities of a passive attacker. In this work, we investigate whether an insider adversary can accurately fingerprint robot movements and operational warehousing workflows via the radio frequency side channel in a stealthy manner. Using an SVM for classification, we found that an adversary can fingerprint individual robot movements with at least 96% accuracy, increasing to near perfect accuracy when reconstructing entire warehousing workflows.