Advertisement

Intrusion Detection for Airborne Communication Using PHY-Layer Information

  • Martin Strohmeier
  • Vincent Lenders
  • Ivan Martinovic
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9148)

Abstract

With passenger and cargo traffic growing rapidly world-wide, and unmanned aerial vehicles (UAV) poised to enter commercial airspaces, a secure next generation of air traffic management systems is required. Recent articles in the academic and hacker community highlight crucial security challenges faced by integral parts of these next generation protocols, with the most dangerous attacks based on classic message injection. In this article, we analyze the possibility and effectiveness of detecting such attacks on critical air traffic infrastructures with a single receiver based on physical layer information. Using hypothesis testing and anomaly detection schemes, we develop an intrusion detection system (IDS) that can accurately detect attackers within 40 s.

Keywords

Unmanned Aerial Vehicle Receive Signal Strength Anomaly Detection Intrusion Detection System International Civil Aviation Organization 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

References

  1. 1.
    Cardenas, A.A., Amin, S., Lin, Z.S., Huang, Y.L., Huang, C.Y., Sastry, S.: Attacks against process control systems: risk assessment, detection, and response. In: Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security, pp. 355–366. ACM (2011)Google Scholar
  2. 2.
    Chen, Y., Xu, W., Trappe, W., Zhang, Y.: Attack detection in wireless localization. In: Chen, Y., Xu, W., Trappe, W., Zhang, Y. (eds.) Securing Emerging Wireless Systems, pp. 1–22. Springer, USA (2009)CrossRefGoogle Scholar
  3. 3.
    Clayton, M.: Malaysia airlines flight MH370: are planes vulnerable to cyber-attack? Christian Science Monitor, March 2014Google Scholar
  4. 4.
    Costin, A., Francillon, A.: Ghost in the air (Traffic): on insecurity of ADS-B protocol and practical attacks on ADS-B devices. In: Black Hat. USA (2012)Google Scholar
  5. 5.
    ICAO: Guidance Material on Comparison of Surveillance Technologies (GMST). Technical report, September 2007Google Scholar
  6. 6.
    Kunkel, R.: Air traffic control insecurity 2.0. In: DefCon 18 (2010)Google Scholar
  7. 7.
    McCallie, D., Butts, J., Mills, R.: Security analysis of the ADS-B implementation in the next generation air transportation system. Int. J. Crit. Infrastruct. Prot. 4(2), 78–87 (2011)CrossRefGoogle Scholar
  8. 8.
    Moran, N., De Vynck, G.: Westjet hijack signal called false alarm. Bloomberg, January 2015Google Scholar
  9. 9.
    RTCA Inc.: Minimum Operational Performance Standards for 1090 MHz Extended Squitter Automatic Dependent Surveillance - Broadcast (ADS-B) and Traffic Information Services - Broadcast (TIS-B). DO-260B with Corrig. 1 (2011)Google Scholar
  10. 10.
    Schäfer, M., Lenders, V., Martinovic, I.: Experimental analysis of attacks on next generation air traffic communication. In: Jacobson, M., Locasto, M., Mohassel, P., Safavi-Naini, R. (eds.) ACNS 2013. LNCS, vol. 7954, pp. 253–271. Springer, Heidelberg (2013) CrossRefGoogle Scholar
  11. 11.
    Schäfer, M., Strohmeier, M., Lenders, V., Martinovic, I., Wilhelm, M.: Bringing up opensky: a large-scale ADS-B sensor network for research. In: ACM/IEEE International Conference on Information Processing in Sensor Networks (2014)Google Scholar
  12. 12.
    Sheng, Y., Tan, K., Chen, G., Kotz, D., Campbell, A.: Detecting 802.11 MAC layer spoofing using received signal strength. In: The 27th Conference on Computer Communications. INFOCOM 2008. IEEE (2008)Google Scholar
  13. 13.
    Strohmeier, M., Lenders, V., Martinovic, I.: On the security of the automatic dependent surveillance-broadcast protocol. Communications Surveys Tutorials PP(99). IEEE (2014)Google Scholar
  14. 14.
    Strohmeier, M., Schäfer, M., Lenders, V., Martinovic, I.: Realities and challenges of nextgen air traffic management: the case of ADS-B. Commun. Mag. 52(5), 111–118 (2014)CrossRefGoogle Scholar
  15. 15.
    Zetter, K.: Air traffic controllers pick the wrong week to quit using radar. In: Wired, July 2012Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Martin Strohmeier
    • 1
  • Vincent Lenders
    • 2
  • Ivan Martinovic
    • 1
  1. 1.University of OxfordOxfordUK
  2. 2.ArmasuisseThunSwitzerland

Personalised recommendations