Guaranteeing spoof-resilient multi-robot networks

• Published in: Autonomous robots Vol. 41; no. 6; pp. 1383 - 1400
• Main Authors: Gil, Stephanie, Kumar, Swarun, Mazumder, Mark, Katabi, Dina, Rus, Daniela
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.08.2017; Springer Nature B.V
• Subjects: Algorithms; Artificial Intelligence; Clients; Computer Imaging; Control; Cryptography; Cybersecurity; Engineering; Mechatronics; Multiple robots; Pattern Recognition and Graphics; Robotics; Robotics and Automation; Robots; Special Issue on "Robotics: Science and Systems"; Vision; Wireless communications; Wireless networks; Anechoic chamber; Wireless networks; Coordinated control; Performance bounds; Cybersecurity; Multi-robot systems; Sybil attack
• ISSN: 0929-5593; 1573-7527
• DOI: 10.1007/s10514-017-9621-5

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%.