TY - GEN
T1 - Guaranteeing spoof-resilient multi-robot networks
AU - Gil, Stephanie
AU - Kumar, Swarun
AU - Mazumder, Mark
AU - Katabi, Dina
AU - Rus, Daniela
N1 - Funding Information:
This work was partially supported by the NSF and MAST project (ARL grant W911NF-08-2-0004). We thank members of the MIT Center for Wireless Networks and Mobile Computing: Amazon.com, Cisco, Google, Intel, MediaTek, Microsoft, and Telefonica for their interest and general support.
Funding Information:
Acknowledgement: This work was partially supported by the NSF and MAST project (ARL grant W911NF-08-2-0004). We thank members of the MIT Center for Wireless Networks and Mobile Computing: Amazon.com, Cisco, Google, Intel, MediaTek, Microsoft, and Telefonica for their interest and general support.
Publisher Copyright:
© 2015, MIT Press Journals. All rights reserved.
PY - 2015
Y1 - 2015
N2 - 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 robotic coverage problems. We experimentally validate our claims using a team of AscTec quadrotor servers and iRobot Create ground clients, and demonstrate spoofer detection rates over 96%.
AB - 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 robotic coverage problems. We experimentally validate our claims using a team of AscTec quadrotor servers and iRobot Create ground clients, and demonstrate spoofer detection rates over 96%.
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U2 - 10.15607/RSS.2015.XI.020
DO - 10.15607/RSS.2015.XI.020
M3 - Conference contribution
AN - SCOPUS:84941917052
T3 - Robotics: Science and Systems
BT - Robotics
A2 - Buchli, Jonas
A2 - Hsu, David
A2 - Kavraki, Lydia E.
PB - MIT Press Journals
T2 - 2015 Robotics: Science and Systems Conference, RSS 2015
Y2 - 13 July 2015 through 17 July 2015
ER -