Injected and Delivered: Fabricating Implicit Control over Actuation Systems by Spoofing Inertial Sensors

TL;DR

This paper demonstrates how acoustic out-of-band signals can be used to manipulate MEMS inertial sensors, exposing vulnerabilities in control systems that rely on these sensors, with successful attacks on most tested devices.

Contribution

It introduces novel methods for controlling inertial sensor outputs via acoustic signals, considering real-world factors like sample rate drift, and demonstrates practical attacks on embedded MEMS sensors.

Findings

17 out of 25 devices were successfully controlled

Controlled manipulation affected inertial data and control systems

Low-frequency signals can also be used to manipulate sensor outputs

Abstract

Inertial sensors provide crucial feedback for control systems to determine motional status and make timely, automated decisions. Prior efforts tried to control the output of inertial sensors with acoustic signals. However, their approaches did not consider sample rate drifts in analog-to-digital converters as well as many other realistic factors. As a result, few attacks demonstrated effective control over inertial sensors embedded in real systems. This work studies the out-of-band signal injection methods to deliver adversarial control to embedded MEMS inertial sensors and evaluates consequent vulnerabilities exposed in control systems relying on them. Acoustic signals injected into inertial sensors are out-of-band analog signals. Consequently, slight sample rate drifts could be amplified and cause deviations in the frequency of digital signals. Such deviations result in fluctuating sensor output; nevertheless, we characterize two methods to control the output: digital amplitude adjusting and phase pacing. Based on our analysis, we devise non-invasive attacks to manipulate the sensor output as well as the derived inertial information to deceive control systems. We test 25 devices equipped with MEMS inertial sensors and find that 17 of them could be implicitly controlled by our attacks. Furthermore, we investigate the generalizability of our methods and show the possibility to manipulate the digital output through signals with relatively low frequencies in the sensing channel.