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


Yazhou Tu, University of Louisiana at Lafayette; Zhiqiang Lin, Ohio State University; Insup Lee, University of Pennsylvania; Xiali Hei, University of Louisiana at Lafayette


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.

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@inproceedings {217565,
author = {Yazhou Tu and Zhiqiang Lin and Insup Lee and Xiali Hei},
title = {Injected and Delivered: Fabricating Implicit Control over Actuation Systems by Spoofing Inertial Sensors},
booktitle = {27th USENIX Security Symposium (USENIX Security 18)},
year = {2018},
isbn = {978-1-939133-04-5},
address = {Baltimore, MD},
pages = {1545--1562},
url = {},
publisher = {USENIX Association},
month = aug

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