Fast Sequence Component Analysis for Attack Detection in Smart Grid

Jordan Landford, Rich Meier, Richard Barella, Scott Wallace, Xinghui Zhao, Eduardo Cotilla-Sanchez, Robert B. Bass

Abstract

Modern power systems have begun integrating synchrophasor technologies into part of daily operations. Given the amount of solutions offered and the maturity rate of application development it is not a matter of “if” but a matter of “when” in regards to these technologies becoming ubiquitous in control centers around the world. While the benefits are numerous, the functionality of operator-level applications can easily be nullified by injection of deceptive data signals disguised as genuine measurements. Such deceptive action is a common precursor to nefarious, often malicious activity. A correlation coefficient characterization and machine learning methodology are proposed to detect and identify injection of spoofed data signals. The proposed method utilizes statistical relationships intrinsic to power system parameters, which are quantified and presented. Several spoofing schemes have been developed to qualitatively and quantitatively demonstrate detection capabilities.

References

  1. Amor, N. B., Benferhat, S., and Elouedi, Z. (2004). Naive bayes vs decision trees in intrusion detection systems. In Proc. ACM Symp. Appl. Comput., pages 420-424. ACM.
  2. Bonebrake, C. and ONeil, L. (2014). Attacks on GPS time reliability. IEEE Security Privacy, 12(3):82-84.
  3. Chang, C.-C. and Lin, C.-J. (2011). Libsvm: A library for support vector machines. ACM Trans. Intelligent Syst. and Technol., 2(3):27.
  4. Chen, T. and Abu-Nimeh, S. (2011). Lessons from stuxnet. Computer, 44(4):91-93.
  5. Cortes, C. and Vapnik, V. (1995). Support-vector networks. Mach. Learn., 20(3):273-297.
  6. De La Ree, J., Centeno, V., Thorp, J., and Phadke, A. (2010). Synchronized phasor measurement applications in power systems. IEEE Trans. Smart Grid, 1(1):20-27.
  7. Humphreys, T. (2009). Assessing the spoofing threat. GPS World, 20(1):28-38.
  8. IEEE (2006). IEEE standard for synchrophasors for power syst. IEEE Std C37.118-2005, pages 1-57.
  9. Jiang, X., Zhang, J., Harding, B., Makela, J., and Dominguez-Garcia, A. (2013a). Spoofing gps receiver clock offset of phasor measurement units. IEEE Trans. Power Syst., 28(3):3253-3262.
  10. Jiang, X., Zhang, J., Harding, B. J., Makela, J. J., and Dominguez-Garcia, A. D. (2013b). Spoofing GPS receiver clock offset of phasor measurement units. IEEE Trans. Power Syst., 28(3):3253-3262.
  11. Kher, S., Nutt, V., Dasgupta, D., Ali, H., and Mixon, P. (2012). A detection model for anomalies in smart grid with sensor network. In Future of Instrumentation Int. Workshop, 2012, pages 1-4. IEEE.
  12. Kim, J., Tong, L., and Thomas, R. J. (2014). Data framing attack on state estimation. IEEE J. Sel. Areas Commun., 32(7).
  13. Kim, J., Tong, L., and Thomas, R. J. (2015). Subspace method for data attack on state estimation: Datadriven approach. IEEE Trans. Signal Process., 63(5).
  14. Kushner, D. (2013). The real story of stuxnet. IEEE Spectr., 50(3):48-53.
  15. Langner, R. (2011). Stuxnet: Dissecting a cyberwarfare weapon. IEEE Security Privacy, 9(3):49-51.
  16. Magiera, J. and Katulski, R. (2013). Accuracy of differential phase delay estimation for gps spoofing detection. In 36th Int. Conf. Telecommun. and Signal Process., pages 695-699.
  17. Meier, R., Histand, M., Landford, J., McCamish, B., Chiu, D., Bass, R., and Cotilla-Sanchez, E. (2014). Managing PMU data sets with bitmap indexes. In IEEE Conf. on Technol. for Sustain., Portland, OR.
  18. Mitchell, R., Chen, I., et al. (2013). Effect of intrusion detection and response on reliability of cyber physical systems. IEEE Trans. Rel., 62(1):199-210.
  19. Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., Vanderplas, J., Passos, A., Cournapeau, D., Brucher, M., Perrot, M., and Duchesnay, E. (2011). Scikit-learn: Machine learning in Python. J. Mach. Learn. Res., 12:2825-2830.
  20. Petit, J., Feiri, M., and Kargl, F. (2011). Spoofed data detection in vanets using dynamic thresholds. In IEEE Vehicular Networking Conf., pages 25-32.
  21. Phadke, A. (2002). Synchronized phasor measurements-a historical overview. In IEEE PES Asia Pacific Transmission and Distribution Conf. and Exhibition, volume 1, pages 476-479 vol.1.
  22. Psiaki, M., O'Hanlon, B., Bhatti, J., Shepard, D., and Humphreys, T. (2013). Gps spoofing detection via dual-receiver correlation of military signals. IEEE Trans. Aerosp. Electron. Syst., 49(4):2250-2267.
  23. Shepard, D., Humphreys, T., and Fansler, A. (2012). Evaluation of the vulnerability of phasor measurement units to gps spoofing attacks. In Int. Conf. Critical Infrastructure Protection, Washington, DC, USA.
  24. Steinmetz, C. P. (1893). Complex quantities and their use in electrical engineering. In Proc. American Institute of Electrical Engineers, pages 33-74, Chicago, IL.
  25. Vu, K., Begovic, M., Novosel, D., and Saha, M. (1999). Use of local measurements to estimate voltage-stability margin. IEEE Trans. Power Syst., 14(3):1029-1035.
  26. Warner, J. and Johnston, R. (2002). A simple demonstration that the global positioning system (gps) is vulnerable to spoofing. J. Security Admin., 25:19-28.
  27. Zhang, Z., Gong, S., Li, H., Pei, C., Zeng, Q., and Jin, M. (2011). Time stamp attack on wide area monitoring system in smart grid. In Comput. Res. Repository.
  28. Zhang, Z., S.Gong, A.D.Dimitrovski, and H.Li (2013). Time synchronization attack in smart grid: Impact and analysis. IEEE Trans. Smart Grid, 4(1):87-98.
Download


Paper Citation


in Harvard Style

Landford J., Meier R., Barella R., Wallace S., Zhao X., Cotilla-Sanchez E. and Bass R. (2016). Fast Sequence Component Analysis for Attack Detection in Smart Grid . In Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS, ISBN 978-989-758-184-7, pages 225-232. DOI: 10.5220/0005860302250232


in Bibtex Style

@conference{smartgreens16,
author={Jordan Landford and Rich Meier and Richard Barella and Scott Wallace and Xinghui Zhao and Eduardo Cotilla-Sanchez and Robert B. Bass},
title={Fast Sequence Component Analysis for Attack Detection in Smart Grid},
booktitle={Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,},
year={2016},
pages={225-232},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005860302250232},
isbn={978-989-758-184-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 5th International Conference on Smart Cities and Green ICT Systems - Volume 1: SMARTGREENS,
TI - Fast Sequence Component Analysis for Attack Detection in Smart Grid
SN - 978-989-758-184-7
AU - Landford J.
AU - Meier R.
AU - Barella R.
AU - Wallace S.
AU - Zhao X.
AU - Cotilla-Sanchez E.
AU - Bass R.
PY - 2016
SP - 225
EP - 232
DO - 10.5220/0005860302250232