Software-based realtime recovery from sensor attacks on robotic vehicles

Hongjun Choi, Sayali Kate, Yousra Aafer, Xiangyu Zhang, Dongyan Xu

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

48 Scopus citations

Abstract

We present a novel technique to recover robotic vehicles (RVs) from various sensor attacks with so-called software sensors. Specifically, our technique builds a predictive state-space model based on the generic system identification technique. Sensor measurement prediction based on the state-space model runs as a software backup of the corresponding physical sensor. When physical sensors are under attacks, the corresponding software sensors can isolate and recover the compromised sensors individually to prevent further damage. We apply our prototype to various sensor attacks on six RV systems, including a real quadrotor and a rover. Our evaluation results demonstrate that our technique can practically and safely recover the vehicle from various attacks on multiple sensors under different maneuvers, preventing crashes.

Original languageEnglish
Title of host publicationRAID 2020 Proceedings - 23rd International Symposium on Research in Attacks, Intrusions and Defenses
PublisherUSENIX Association
Pages349-364
Number of pages16
ISBN (Electronic)9781939133182
StatePublished - 2020
Event23rd International Symposium on Research in Attacks, Intrusions and Defenses, RAID 2020 - Virtual, Online
Duration: 14 Oct 202016 Oct 2020

Publication series

NameRAID 2020 Proceedings - 23rd International Symposium on Research in Attacks, Intrusions and Defenses

Conference

Conference23rd International Symposium on Research in Attacks, Intrusions and Defenses, RAID 2020
CityVirtual, Online
Period14/10/2016/10/20

Bibliographical note

Publisher Copyright:
© 2020 by The USENIX Association. All Rights Reserved.

Fingerprint

Dive into the research topics of 'Software-based realtime recovery from sensor attacks on robotic vehicles'. Together they form a unique fingerprint.

Cite this