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Using the Physical Layer to Detect Attacks on Building Automation Networks

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Security and Privacy in Communication Networks (SecureComm 2020)

Abstract

This work investigates possible methods of adding security features to building automation networks in the form of intrusion or tamper detection by using the physical layer. This is a concept that is widely known in the field of wireless communications but is—as of now—less prevalent in wired environments. We propose three distinct and complementary methods which rely on electrical fingerprinting of devices and the communication medium, as well as active radio-frequency probing of the network. To assess their effectiveness, we conduct a series of experiments in a building automation system test environment.

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References

  1. Abdi, H., Williams, L.J.: Principal component analysis. WIREs Comput. Stat. 2(4), 433–459 (2010)

    Article  Google Scholar 

  2. Bagci, I.E., Roedig, U., Martinovic, I., Schulz, M., Hollick, M.: Using channel state information for tamper detection in the internet of things. In: Proceedings of the 31st Annual Computer Security Applications Conference, pp. 131–140. Association for Computing Machinery, Los Angeles (2015)

    Google Scholar 

  3. Bevan, D.D., Averin, I., Lysyakov, D.: RF fingerprinting for location estimation. US Patent 8,170,815 B2 (USA). R.B. LP. May 1, 2012. http://patft1.uspto.gov/netacgi/nph-Parser?patentnumber=8170815. Accessed 14 Feb 2020

  4. Brik, V., Banerjee, S., Gruteser, M., Oh, S.: Wireless device identification with radiometric signatures. In: Proceedings of the 14th ACM International Conference on Mobile Computing and Networking, pp. 116–127. Association for Computing Machinery, San Francisco (2008)

    Google Scholar 

  5. Campos, R.S., Lovisolo, L.: RF fingerprinting location techniques (chap. 15). In: Handbook of Position Location, pp. 487–520. Wiley (2011). https://doi.org/10.1002/9781118104750. ISBN 9781118104750

  6. Corrigan, S.: Introduction to the Controller Area Network (CAN). SLOA101B. Application Report. Texas Instruments Incorporated, May 2016. https://www.ti.com/lit/an/sloa101b/sloa101b.pdf. Accessed 07 Feb 2020

  7. Fisher, D., Isler, B., Osborne, M.: BACnet Secure Connect. A Secure Infrastructure for Building Automation. White Paper, version 15. ASHRAE SSPC 135 IT Working Group (2019). https://www.ashrae.org/File%20Library/Technical%20Resources/Bookstore/BACnet-SC-Whitepaper-v15_Final_20190521.pdf. Accessed 03 Apr 2020

  8. Gerdes, R.M., Mina, M., Russell, S.F., Daniels, T.E.: Physical-layer identification of wired ethernet devices. IEEE Trans. Inf. Forensics Secur. 7(4), 1339–1353 (2012)

    Article  Google Scholar 

  9. Granzer, W., Praus, F., Kastner, W.: Security in building automation systems. IEEE Tran. Ind. Electron. 57(11), 3622–3630 (2010)

    Article  Google Scholar 

  10. Gray, P.R., Hurst, P.J., Lewis, S.H., Meyer, R.G.: Noise in integrated circuits (chap. 11). In: Analysis and Design of Analog Integrated Circuits, 5th edn., pp. 736–795. Wiley, January 2009. ISBN 978-0-470-24599-6

    Google Scholar 

  11. KNX on track for success again in 2019: Sector Coupling and IoT in focus. Press Release, KNX Association Cvba (2019). https://media.knx.org/feed/file/1050. Accessed 13 Feb 2020

  12. Lackner, G., Payer, U., Teufl, P.: Combating wireless LAN MAC-layer address spoofing with fingerprinting methods. Int. J. Netw. Secur. 9(2), 164–172 (2009)

    Google Scholar 

  13. Leach, T.: Implementing a BACnet network. ASHRAE J. 59(3), 40–48 (2017)

    Google Scholar 

  14. Maes, R., Verbauwhede, I.: Physically unclonable functions: a study on the state of the art and future research directions. In: Sadeghi, A.R., Naccache, D. (eds.) Towards Hardware-Intrinsic Security. ISC, pp. 3–37. Springer, Heidelberg (2010). https://doi.org/10.1007/978-3-642-14452-3_1. ISBN 978-3-642-14452-3

    Chapter  Google Scholar 

  15. Maximum data protection for smart buildings. Press Release, KNX Association Cvba (2017). https://media.knx.org/feed/file/918. Accessed 03 Apr 2020

  16. Mundt, T., Krüger, F., Wollenberg, T.: Who refuses to wash hands? Privacy issues in modern house installation networks. In: 2012 Seventh International Conference on Broadband, Wireless Computing, Communication and Applications, pp. 271–277 (2012)

    Google Scholar 

  17. NCN5121. Transceiver for KNX Twisted Pair Networks. Rev. 2. Datasheet. Semiconductor Components Industries, LLC, August 2019. https://www.onsemi.com/pub/Collateral/NCN5121-D.PDF. Accessed 17 Feb 2020

  18. PROFIBUS System Description. Technology and Application. 4.332. PROFIBUS Nutzerorganisation e. V. (PNO), April 2016. https://www.profibus.com/index.php?eID=dumpFile&t=f&f=52380&token=4868812e468cd5e71d2a07c7b3da955b47a8e10d Accessed 07 Feb 2020

  19. Sokollik, F., Helm, P., Seela, R.: KNX für die Gebäudesystemtechnik in Wohnund Zweckbau. VDE Verlag GmbH (2017)

    Google Scholar 

  20. Szmulewicz, D.: Using MSP on KNX Systems. SWRA497. Application Report. Texas Instruments Incorporated. December 2015. http://www.ti.com/lit/an/swra497/swra497. pdf. Accessed 17 Feb 2020

  21. Wang, X., Zhang, Y., Zhang, H., Wei, X., Wang, G.: Identification and authentication for wireless transmission security based on RF-DNA fingerprint. EURASIP J. Wirel. Commun. Netw. 2019, 230 (2019). https://doi.org/10.1186/s13638-019-1544-8

    Article  Google Scholar 

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Acknowledgment

This research was funded by a grant from the German Federal Ministry for Economic Affairs and Energy in accordance with a resolution passed by the German federal parliament.

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Correspondence to Andreas Zdziarstek .

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© 2020 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Zdziarstek, A., Brekenfelder, W., Eibisch, F. (2020). Using the Physical Layer to Detect Attacks on Building Automation Networks. In: Park, N., Sun, K., Foresti, S., Butler, K., Saxena, N. (eds) Security and Privacy in Communication Networks. SecureComm 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 336. Springer, Cham. https://doi.org/10.1007/978-3-030-63095-9_24

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  • DOI: https://doi.org/10.1007/978-3-030-63095-9_24

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-030-63095-9

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