Smart Grid Data Integrity Attacks - Berkeley Center for Control and ...

IEEE TRANSACTIONS ON SMART GRID, VOL. 1, NO. 1, JANUARY 2012 10
Fig. 7. IEEE 300 bus test case: 19 bus subsystem.
Fig. 8. 3-Sparse attack that compromises injection buses 9021 and 9002.
The attack commences at t = 3sec with amplitude increasing at 3MW/sec.
all 3-,4-, and 5-sparse attacks under the assumption that all
lines are metered. We have offered countermeasures against
arbitrary unobservable attacks using known-secure PMUs, and
shown that p + 1 PMUs are sufficient to disable p attacks.
A significant difficulty in state estimation is the stale data
problem. Meter readings arrive asynchronously at the state
estimator, and the worst case delay may be on the order of 5-
10 minutes [including algorithm convergence time]. With such
latencies, state estimation may be a poor vehicle to detect
cyberattacks. The deeper issue with cybersecurity research
relate to grid operations. An attack has consequences only
when the grid operator is misled into taking harmful actions
based on the compromised data. A comprehensive and realistic
analysis of cybersecurity threats to electricity grids must
therefore incorporate current operating practice, both under
normal and contingency operations. These issues are worthy
of future research.
REFERENCES
[1] A. Abur and A. G. Exposito, “Power System State Estimation: Theory
and Implementation,” CRC Press, 2004.
[2] M. Basseville and I. V. Nikiforov, “Detection of Abrupt Changes: Theory
and Application,” Prentice-Hall, 1993.
[3] R.B. Bobba, K.M. Rogers, Q. Wang, H. Khurana, K. Nahrstedt and
T.J. Overbye, “Detecting False Data Injection Attacks on DC State
Estimation,” Proceedings First Workshop on Secure Control Systems,
CPSWeek 2010, Stockholm Sweden, April, 2010.
[4] J. Chen and A. Abur, “Placement of PMUs to Enable Bad Data Detection
in State Estimation,” IEEE Transactions on Power Systems, vol. 21, no.
4, pp. 1608–1615, 2006.
[5] S. Cui, Z. Han, S. Kar, T. T. Kim, H. V. Poor, and A. Tajer, “Coordinated
Data Injection Attack and Detection in Smart Grid,” IEEE Signal
Processing Magazine, vol. 29, no. 5, pp. 106–115, 2012.
[6] G. Dan and H. Sandberg, “Stealth Attacks and Protection Schemes for
State Estimators in Power Systems,” Proceedings First IEEE International
Conference on Smart Grid Communications (SmartGridComm),
2010.
[7] S. Dasgupta, C. Papadimitriou, and U. Vazirani, Algorithms, McGraw
Hill, 2006.
[8] Dept. of Energy, http://www.oe.energy.gov/DocumentsandMedia/02-1-
11 OE Press Release Risk Management.pdf
[9] R. Emami and A. Abur, “Robust Measurement Design by Placing Synchronized
Phasor Measurements on Network Branches,” IEEE Transactions
on Power Systems, vol. 25, no. 1, pp. 38–43, Feb. 2010.
[10] T. Flick and J. Morehouse, “Securing the Smart Grid: Next Generation
Power Grid Security,” Syngress, 2010.
[11] A. Giani et al, “Smart Grid Data Integrity Attacks: Characterizations
and Countermeasures,” Proceedings of The Second IEEE International
Conference on Smart Grid Communications (SmartGridComm), 2010.
[12] D. Gorinevsky, S. Boyd, and S. Poll, “Estimation of Faults in DC
Electrical Power System,” Proceedings IEEE Conference on Decision
and Control, pp. 4334–4339, December 2009.
[13] G.P. Granelli, and M. Montagna, “Identification of Interacting Bad Data
in the Framework of the Weighted Least Square Method,” Electric Power
Systems Research, vol. 78, no. 5, pp. 806–814, 2008.
[14] J. Hopcroft and R. Tarjan, “Efficient algorithms for graph manipulation,”
Communications of the ACM, vol. 16, no. 6, pp. 372-378, 1973.
[15] C.-H. Huang, C.-H. Lee, K.-R. Shih, and Y.-J. Wang, “Bad Data Analysis
in Power System Measurement Estimation,” European Transaction on
Electrical Power, vol. 20, pp. 1082–1100, 2010.
[16] H.-J.Koglin, Th. Neisius, G. Beissler, and K. D. Schmitt, “Bad Data
Detection and Identification,” Int. Journal on Electric Power, vol. 12,
no. 2, pp. 94–103, 1990.
[17] V. Igure, S. Laughtera, and R. Williams, “Security issues in SCADA
networks,” Computers and Security, vol. 25, no. 7, pp. 498–506, 2006.
[18] G. N. Korres et al., “Numerical Observability Analysis Based on
Network Graph Theory,” IEEE Transaction on Power Systems, vol. 18,
no. 3, pp. 1035–1045, 2003.
[19] T.T. Kim and H. V. Poor, “Strategic Protection Against Data Injection
Attacks on Power Grids”, IEEE Transactions on Smart Grid, vol. 2, no.
2, pp. 326–333, 2011.
[20] O. Kosut, L. Jia, R. Thomas, and L. Tong, “Malicious Data Attacks on
Smart Grid State Estimation: Attack Strategies and Countermeasures,”
Proceedings First IEEE International Conference on Smart Grid Communications
(SmartGridComm), 2010.