Guaranteeing spoof-resilient multi-robot networks
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10514_2017_9621_ReferencePDF.pdf
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Author(s)
Kumar, Swarun
Mazumder, Mark
Gil, Stephanie
Katabi, Dina
Rus, Daniela L
Date Issued
February 2017
Journal
Autonomous Robots
Publisher
Springer-Verlag
Citation
Gil, Stephanie; Kumar, Swarun; Mazumder, Mark; Katabi, Dina and Rus, Daniela. “Guaranteeing Spoof-Resilient Multi-Robot Networks.” Autonomous Robots 41, 6 (February 2017): 1383–1400 © 2017 Springer Science+Business Media New York
Version
Author's final manuscript
Abstract
Multi-robot networks use wireless communication to provide wide-ranging services such as aerial surveillance and unmanned delivery. However, effective coordination between multiple robots requires trust, making them particularly vulnerable to cyber-attacks. Specifically, such networks can be gravely disrupted by the Sybil attack, where even a single malicious robot can spoof a large number of fake clients. This paper proposes a new solution to defend against the Sybil attack, without requiring expensive cryptographic key-distribution. Our core contribution is a novel algorithm implemented on commercial Wi-Fi radios that can “sense” spoofers using the physics of wireless signals. We derive theoretical guarantees on how this algorithm bounds the impact of the Sybil Attack on a broad class of multi-robot problems, including locational coverage and unmanned delivery. We experimentally validate our claims using a team of AscTec quadrotor servers and iRobot Create ground clients, and demonstrate spoofer detection rates over 96%.
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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DOI of Published Version
https://doi.org/10.1007/s10514-017-9621-5
