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Guaranteeing spoof-resilient multi-robot networks

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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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Notes

  1. The case of adversarial server robots is left for future work although many of the concepts in the current paper are extensible to this case as well.

  2. Detecting if a client i is spoofed becomes easier given more servers communicating with i (i.e., a larger neighborhood \(\mathcal {N}_i\)). But even with a single server, this determination can be made. A theoretical treatment of this point is given in Sect. 5 and experimental results (Sect. 9.1) use as little as one server.

  3. For clarity, we drop dependence on i, l for SNR, \(\sigma _\theta \) and \(\sigma _\phi \).

  4. This is a mild requirement since 25–30 packets can be transmitted in tens of milliseconds, even at the lowest data rate of 6Mb/s of 802.11n Wi-Fi.

References

  • Amazon prime air. http://www.amazon.com/b?node=8037720011.

  • Adib, F., Kumar, S., Aryan, O., Gollakota, S., & Katabi, D. (2013). Interference Alignment by Motion. In MOBICOM.

  • Beard, R., McLain, T., Nelson, D., Kingston, D., & Johanson, D. (2006). Decentralized cooperative aerial surveillance using fixed-wing miniature UAVs. Proceedings of the IEEE, 94(7), 1306–1324. doi:10.1109/JPROC.2006.876930.

    Article  Google Scholar 

  • Chapman, A., Nabi-Abdolyousefi, M., & Mesbahi, M. (2009). Identification and infiltration in consensus-type networks. In 1st IFAC Workshop on Estimation and Control of Networked Systems.

  • Cortes, J., Martinez, S., Karatas, T., & Bullo, F. (2004). Coverage control for mobile sensing networks. IEEE Transactions on Robotics and Automation, 20(2), 243–255. doi:10.1109/TRA.2004.824698.

    Article  Google Scholar 

  • Daniel, K., Dusza, B., Lewandowski, A., & Wietfeld, C. (2009). AirShield: A system-of-systems MUAV remote sensing architecture for disaster response. In Systems conference, 2009 3rd Annual IEEE (pp. 196–200) doi:10.1109/SYSTEMS.2009.4815797.

  • Douceur, J. (2002). The sybil attack. In P. Druschel, F. Kaashoek, & A. Rowstron (Eds.), Peer-to-Peer systems, Lecture Notes in Computer Science (vol. 2429, pp. 251–260). Berlin: Springer. doi:10.1007/3-540-45748-8_24.

  • Fawcett, T. (2004). ROC graphs: Notes and practical considerations for researchers. Technical Report.

  • Feng, Z., Ning, J., Broustis, I., Pelechrinis, K., Krishnamurthy, S.V., & Faloutsos, M. (2011). Coping with packet replay attacks in wireless networks. In Sensor, mesh and ad hoc communications and networks (SECON), 2011 8th Annual IEEE Communications Society Conference on (pp. 368–376). IEEE.

  • Fitch, P. J. (1988). Synthetic aperture radar. Berlin: Springer.

    Book  Google Scholar 

  • Gazzah, H., & Marcos, S. (2003). Directive antenna arrays for 3D source localization. In Signal processing advances in wireless communications, 2003. SPAWC 2003. 4th IEEE Workshop on (pp. 619–623). doi:10.1109/SPAWC.2003.1319035.

  • Gazzah, H., & Marcos, S. (2006). Cramer-Rao bounds for antenna array design. IEEE Transactions on Signal Processing, 54, 336–345. doi:10.1109/TSP.2005.861091.

    Article  Google Scholar 

  • Gil, S., Kumar, S., Katabi, D., & Rus, D. (2013). Adaptive communication in multi-robot systems using directionality of signal strength. ISRR.

  • Gil, S., Kumar, S., Mazumder, M., Katabi, D., & Rus, D. (2015a). Guaranteeing spoof-resilient multi-robot networks. In Full paper version with supplementary material available as a TECH REPORT at MIT CSAIL Publications and Digital Archive. http://publications.csail.mit.edu.

  • Gil, S., Kumar, S., Mazumder, M., Katabi, D., & Rus, D. (2015b). Guaranteeing spoof-resilient multi-robot networks. In Proceedings of robotics: Science and systems. Rome, Italy.

  • Goldsmith, A. (2005). Wireless communications. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Halperin, D., Hu, W., Sheth, A., & Wetherall, D. (2011). Tool release: Gathering 802.11n traces with channel state information. ACM SIGCOMM. Computer Communication Review, 41(1), 53.

    Article  Google Scholar 

  • Hayes, M. H. (1996). Statistical digital signal processing and modeling (1st ed.). New York, NY, USA: Wiley.

    Google Scholar 

  • Higgins, F., Tomlinson, A., & Martin, K.M. (2009). Threats to the swarm: Security considerations for swarm robotics. International Journal on Advances in Security, 2.

  • Jin, D., & Song, J. (2014). A traffic flow theory aided physical measurement-based sybil nodes detection mechanism in vehicular ad-hoc networks. In Computer and information science (ICIS), 2014 IEEE/ACIS 13th international conference on (pp. 281–286). doi:10.1109/ICIS.2014.6912147. URL http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6912147&tag=1.

  • Klausing, H. (1989). Feasibility of a SAR with rotating antennas (ROSAR). In Microwave Conference, 1989.

  • Kumar, S., Gil, S., Katabi, D., & Rus, D. (2014). Accurate indoor localization with zero start-up cost. In Proceedings of the 20th annual international conference on mobile computing and networking, MobiCom ’14 (pp. 483–494). New York, NY, USA: ACM. doi:10.1145/2639108.2639142.

  • Kumar, S., Hamed, E., Katabi, D., & Erran Li, L. (2014). LTE radio analytics made easy and accessible. In Proceedings of the 2014 ACM conference on SIGCOMM, SIGCOMM ’14 (pp. 211–222). New York, NY, USA: ACM. doi:10.1145/2619239.2626320.

  • Laporte, G., Nobert, Y., & Taillefer, S. (1988). Solving a family of multi-depot vehicle routing and location-routing problems. Transportation Science, 22(3), 161–172.

    Article  MathSciNet  MATH  Google Scholar 

  • Levine, B. N., Shields, C., & Margolin, N. B. (2006). A survey of solutions to the sybil attack. Techincal Report, Document Number 2006-052. Amherst: University of Massachusetts Amherst

  • Lin, L., & Goodrich, M. A. (2009). UAV intelligent path planning for wilderness search and rescue. In Intelligent robots and systems, 2009. IROS 2009. IEEE/RSJ International Conference on (pp. 709–714). IEEE.

  • Liu, H., Wang, Y., Liu, J., Yang, J., & Chen, Y. (2014). Practical user authentication leveraging channel state information (CSI). In Proceedings of the 9th ACM symposium on information, computer and communications security, ASIA CCS ’14 (pp. 389–400). New York, NY, USA: ACM. doi:10.1145/2590296.2590321.

  • Liu, X., Li, A., Yang, X., & Wetherall, D. (2008). Passport: Secure and adoptable source authentication. In Proceedings of the 5th USENIX Symposium on Networked Systems Design and Implementation, NSDI’08 (pp. 365–378). Berkeley, CA, USA: USENIX Association. http://dl.acm.org/citation.cfm?id=1387589.1387615.

  • Liu, Y., Bild, D., Dick, R., Mao, Z.M., & Wallach, D. (2014). The Mason test: A defense against Sybil attacks in wireless networks without trusted authorities. CORR, abs/1403.5871. http://dblp.unitrier.de/rec/bib/journals/corr/LiuBDMW14.

  • Malmirchegini, M., & Mostofi, Y. (2012). On the spatial predictability of communication channels. IEEE Transactions on Wireless Communications, 11(3), 964–978.

    Article  Google Scholar 

  • Mathews, C. P., & Zoltowsk, M. D. (1994). Signal Subspace Techniques for Source Localization with Circular Sensor Arrays. Purdue University TechReport. http://docs.lib.purdue.edu/cgi/viewcontent.cgi?article=1175&context=ecetr

  • Miao, F., Pajic, M., & Pappas, G.J. (2013). Stochastic game approach for replay attack detection. In Decision and control (CDC), 2013 IEEE 52nd annual conference on (pp. 1854–1859). IEEE.

  • Newsome, J., Shi, E., Song, D., & Perrig, A. (2004). The sybil attack in sensor networks: Analysis defenses. In Information processing in sensor networks, 2004. IPSN 2004. Third international symposium on (pp. 259–268). doi:10.1109/IPSN.2004.1307346.

  • Olfati-Saber, R., & Murray, R. (2004). Consensus problems in networks of agents with switching topology and time-delays. IEEE Transactions on Automatic Control, 49(9), 1520–1533. doi:10.1109/TAC.2004.834113.

    Article  MathSciNet  Google Scholar 

  • Parker, L. E. (2002). Distributed algorithms for multi-robot observation of multiple moving targets. Autonomous Robots, 12, 231–255.

    Article  MATH  Google Scholar 

  • Pavone, M., Frazzoli, E., & Bullo, F. (2011). Adaptive and distributed algorithms for vehicle routing in a stochastic and dynamic environment. IEEE Transactions on Automatic Control, 56(6), 1259–1274.

    Article  MathSciNet  Google Scholar 

  • Pires W. R., de Paula Figueiredo, T., Wong, H., & Loureiro, A. (2004). Malicious node detection in wireless sensor networks. In Parallel and distributed processing symposium, 2004. Proceedings. 18th international (p. 24). doi:10.1109/IPDPS.2004.1302934.

  • Sargeant, I., & Tomlinson, A. (2013). Modelling malicious entities in a robotic swarm. In Digital avionics systems conference (DASC), 2013 IEEE/AIAA 32nd.

  • Schwager, M., Julian, B. J., & Rus, D. (2009). Optimal coverage for multiple hovering robots with downward facing cameras. In Robotics and automation, 2009. ICRA ’09. IEEE international conference on (pp. 3515–3522). doi:10.1109/ROBOT.2009.5152815.

  • Schwager, M., Rus, D., & Slotine, J. J. (2009). Decentralized, adaptive coverage control for networked robots. The International Journal of Robotics Research, 28(3), 357–375. http://ijr.sagepub.com/content/28/3/357.abstract.

  • Sheng, Y., Tan, K., Chen, G., Kotz, D., & Campbell, A. (2008). Detecting 802.11 MAC layer spoofing using received signal strength. In INFOCOM 2008. The 27th Conference on Computer Communications. IEEE. doi:10.1109/INFOCOM.2008.239. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4509834&tag=1.

  • Stoica, P., & Arye, N. (1989). Music, maximum likelihood, and Cramer-Rao bound. IEEE Transactions on Acoustics, Speech and Signal Processing, 37(5), 720–741. doi:10.1109/29.17564.

    Article  MathSciNet  MATH  Google Scholar 

  • Tse, D., & Vishwanath, P. (2005). Fundamentals of wireless communications. Cambridge: Cambridge University Press.

    Book  Google Scholar 

  • Wang, J., & Katabi, D. (2013). Dude, Where’s my card?: RFID positioning that works with multipath and non-line of sight. In SIGCOMM.

  • Wang, T., & Yang, Y. (2013). Analysis on perfect location spoofing attacks using beamforming. In INFOCOM, 2013 Proceedings IEEE (pp. 2778–2786). doi:10.1109/INFCOM.2013.6567087. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6567087.

  • Wang, X., Yadav, V., & Balakrishnan, S. (2007). Cooperative UAV formation flying with obstacle/collision avoidance. IEEE Transactions on Control Systems Technology, 15(4), 672–679.

    Article  Google Scholar 

  • Wang, Y., Attebury, G., & Ramamurthy, B. (2006). A survey of security issues in wireless sensor networks. Communications Surveys Tutorials, IEEE, 8(2), 2–23. doi:10.1109/COMST.2006.315852.

    Article  Google Scholar 

  • Xiao, L., Greenstein, L., Mandayam, N. B., & Trappe, W. (2009). Channel-based detection of sybil attacks in wireless networks. IEEE Transactions on Information Forensics and Security, 4(3), 492–503. doi:10.1109/TIFS.2009.2026454.

    Article  Google Scholar 

  • Xiong, J., & Jamieson, K. (2013). SecureArray: Improving Wifi security with fine-grained physical-layer information. In Proceedings of the 19th annual international conference on mobile computing & networking, MobiCom ’13 (pp. 441–452). New York, NY, USA: ACM. doi:10.1145/2500423.2500444.

  • Yang, J., Chen, Y., Trappe, W., & Cheng, J. (2013). Detection and localization of multiple spoofing attackers in wireless networks. IEEE Transactions on Parallel and Distributed Systems, 24(1), 44–58. doi:10.1109/TPDS.2012.104.

    Article  Google Scholar 

  • Yang, Z., Ekici, E., & Xuan, D. (2007). A localization-based anti-sensor network system. In INFOCOM 2007. 26th IEEE international conference on computer communications (pp. 2396–2400). IEEE, doi:10.1109/INFCOM.2007.288. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4215870.

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Acknowledgements

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.

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Correspondence to Stephanie Gil.

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This is one of several papers published in Autonomous Robots comprising the “Special Issue on Robotics Science and Systems”.

Stephanie Gil and Swarun Kumar: Co-primary authors.

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Gil, S., Kumar, S., Mazumder, M. et al. Guaranteeing spoof-resilient multi-robot networks. Auton Robot 41, 1383–1400 (2017). https://doi.org/10.1007/s10514-017-9621-5

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