Guaranteeing spoof-resilient multi-robot networks
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...
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| Veröffentlicht in: | Autonomous robots Jg. 41; H. 6; S. 1383 - 1400 |
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| 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%. |
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| AbstractList | 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%. |
| Author | Katabi, Dina Gil, Stephanie Kumar, Swarun Rus, Daniela Mazumder, Mark |
| Author_xml | – sequence: 1 givenname: Stephanie surname: Gil fullname: Gil, Stephanie email: sgil@mit.edu organization: Massachusetts Institute of Technology – sequence: 2 givenname: Swarun surname: Kumar fullname: Kumar, Swarun organization: Carnegie Mellon University – sequence: 3 givenname: Mark surname: Mazumder fullname: Mazumder, Mark organization: MIT Lincoln Laboratory – sequence: 4 givenname: Dina surname: Katabi fullname: Katabi, Dina organization: Massachusetts Institute of Technology – sequence: 5 givenname: Daniela surname: Rus fullname: Rus, Daniela organization: Massachusetts Institute of Technology |
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| Keywords | Anechoic chamber Wireless networks Coordinated control Performance bounds Cybersecurity Multi-robot systems Sybil attack |
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