Energy Big Data Analytics and Security: Challenges and Opportunities

IEEE Transactions on Smart Grid

Volumn 7, Issue 5, 2016, Pages 2423-2436

  Hu, Jiankun ^a   Vasilakos, Athanasios V ^b  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

^b LULEÅ UNIVERSITY OF TECHNOLOGY   (Sweden)

Author keywords

analytics; anomaly detection; big data; cyber security; Energy; SCOPF; smart grid

Indexed keywords

ANOMALY DETECTION; BIG DATA; DATA ANALYTICS; ELECTRIC POWER TRANSMISSION NETWORKS; FOSSIL FUELS;

ANALYTICS; CYBER SECURITY; ENERGY; SCOPF; SMART GRID;

SMART POWER GRIDS;

EID: 84984631748     PISSN: 19493053     EISSN: 19493061     Source Type: Journal    
DOI: 10.1109/TSG.2016.2563461     Document Type: Article

References (88)

1. Ecotricity. The End of Fossil Fuels. Accessed on Jul. 21, 2015. [Online]. Available: https://www.ecotricity.co.uk/our-green-energy/energy-independence/the-end-of-fossil-fuels
2. J. Hu, H. R. Pota, and S. Guo, "Taxonomy of attacks for agentbased smart grids, " IEEE Trans. Parallel Distrib. Syst., vol. 25, no. 7, pp. 1886-1895, Jul. 2014.
3. N. Bui, A. P. Castellani, P. Casari, and M. Zorzi, "The Internet of energy: A Web-enabled smart grid system, " IEEE Netw., vol. 26, no. 4, pp. 39-45, Jul./Aug. 2012.
4. D. Alahakoon and X. Yu, "Smart electricity meter data intelligence for future energy systems: A survey, " IEEE Trans. Ind. Informat., vol. 12, no. 1, pp. 425-436, Feb. 2016, doi: 10.1109/TII.2015.2414355.
5. Z. Huang, H. Luo, D. Skoda, T. Zhu, and Y. Gu, "E-Sketch: Gathering large-scale energy consumption data based on consumption patterns, " in Proc. IEEE Int. Conf. Big Data (Big Data), Washington, DC, USA, 2014, pp. 656-665.
6. J. Yin, P. Sharma, I. Gorton, and B. Akyoli, "Large-scale data challenges in future power grids, " in Proc. IEEE 7th Int. Symp. Service Orient. Syst. Eng. (SOSE), Redwood City, CA, USA, 2013, pp. 324-328.
7. M. Aiello and G. A. Pagani, "The smart grid's data generating potentials, " in Proc. Federated Conf. Comput. Sci. Inf. Syst. (FedCSIS), Warsaw, Poland, 2014, pp. 9-16.
8. K. L. Wagstaff, "Machine learning that matters, " in Proc. 29th Int. Conf. Mach. Learn. (ICML), Pasadena, CA, USA, 2012, pp. 529-536.
9. D. A. Powner, "Electricity grid modernization: Progress being made on cybersecurity guidelines, but key challenges remain to be addressed, GAO report, " United States Gov. Account. Office, Washington, DC, USA, Tech. Rep. GAO-11-117, Jan. 2011. [Online]. Available: http://www.gao.gov/new.items/d11117.pdf
10. S. Simitis, "From the market to the polis: The EU directive on the protection of personal data, " Iowa Law. Rev., vol. 80, no. 3, p. 445, 1994.
11. S. Bera, S. Misra, and J. J. P. C. Rodrigues, "Cloud computing applications for smart grid: A survey, " IEEE Trans. Parallel Distrib. Syst., vol. 26, no. 5, pp. 1477-1494, May 2015.
12. J. W. Taylor and P. E. McSharry, "Short-Term load forecasting methods: An evaluation based on european data, " IEEE Trans. Power Syst., vol. 22, no. 4, pp. 2213-2219, Nov. 2007.
13. M. Frincu, C. Chelmis, M. U. Noor, and V. Prasanna, "Accurate and efficient selection of the best consumption prediction method in smart grids, " in Proc. IEEE Int. Conf. Big Data (Big Data), Washington, DC, USA, 2014, pp. 721-729.
14. S. Aman, Y. Simmhan, and V. K. Prasanna, "Holistic measures for evaluating prediction models in smart grids, " IEEE Trans. Knowl. Data Eng., vol. 27, no. 2, pp. 475-488, Feb. 2015.
15. K. Nose-Filho, A. D. P. Lotufo, and C. R. Minussi, "Short-Term multinodal load forecasting using a modified general regression neural network, " IEEE Trans. Power Del., vol. 26, no. 4, pp. 2862-2869, Oct. 2011.
16. L. Ghelardoni, A. Ghio, and D. Anguita, "Energy load forecasting using empirical mode decomposition and support vector regression, " IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 549-556, Mar. 2013.
17. T. Senjyu, P. Mandal, K. Uezato, and T. Funabashi, "Next day load curve forecasting using hybrid correction method, " IEEE Trans. Power Syst., vol. 20, no. 1, pp. 102-109, Feb. 2005.
18. Y. Chen et al., "Short-Term load forecasting: Similar day-based wavelet neural networks, " IEEE Trans. Power Syst., vol. 25, no. 1, pp. 322-330, Feb. 2010.
19. R. E. Abdel-Aal, "Short-Term hourly load forecasting using abductive networks, " IEEE Trans. Power Syst., vol. 19, no. 1, pp. 164-173, Feb. 2004.
20. S. Li, P. Wang, and L. Goel, "A novel wavelet-based ensemble method for short-Term load forecasting with hybrid neural networks and feature selection, " IEEE Trans. Power Syst., vol. 31, no. 3, pp. 1788-1798, May 2016.
21. A. Bracale, P. Caramia, G. Carpinelli, A. R. Di Fazio, and P. Varilone, "A bayesian-based approach for a short-Term steady-state forecast of a smart grid, " IEEE Trans. Smart Grid, vol. 4, no. 4, pp. 1760-1771, Dec. 2013.
22. W. Lee, B.-W. On, I. Lee, and J. Choi, "A big data management system for energy consumption prediction models, " in Proc. 9th Int. Conf. Digital Inf. Manag. (ICDIM), 2014, pp. 156-161.
23. R. Christie, "Power systems test case archive, " Dept. Elect. Eng., Univ. Washington, Seattle, WA, USA, 2000. [Online]. Available: http://www.ee.washington.edu/research/pstca/
24. M. Shahidehpour, F. Tinney, and Y. Fu, "Impact of security on power systems operation, " Proc. IEEE, vol. 93, no. 11, pp. 2013-2025, Nov. 2005.
25. N. Balu et al., "On-line power system security analysis, " Proc. IEEE, vol. 80, no. 2, pp. 262-282, Feb. 1992.
26. K. J. Ross, K. M. Hopkinson, and M. Pachter, "Using a distributed agent-based communication enabled special protection system to enhance smart grid security, " IEEE Trans. Smart Grid, vol. 4, no. 2, pp. 1216-1224, Jun. 2013.
27. C. Vellaithurai, A. Srivastava, S. Zonouz, and R. Berthier, "CPINDEX: Cyber-physical vulnerability assessment for power-grid infrastructures, " IEEE Trans. Smart Grid, vol. 6, no. 2, pp. 566-575, Mar. 2015.
28. D. Kundur, X. Feng, S. Liu, T. Zourntos, and K. L. Butler-Purry, "Towards a framework for cyber attack impact analysis of the electric smart grid, " in Proc. 1st IEEE Int. Conf. Smart Grid Commun. (SmartGridComm), Gaithersburg, MD, USA, 2010, pp. 244-249.
29. J. Fadul, K. Hopkinson, C. Sheffield, J. Moore, and T. Andel, "Trust management and security in the future communication-based 'smart' electric power grid, " in Proc. 44th Hawaii Int. Conf. Syst. Sci. (HICSS), 2011, pp. 1-10.
30. J. Hu, I. Khalil, S. Han, and A. Mahmood, "Seamless integration of dependability and security concepts in SOA: A feedback control system based framework and taxonomy, " J. Netw. Comput. Appl., vol. 34, no. 4, pp. 1150-1159, 2011.
31. J. Baek, Q. H. Vu, J. K. Liu, X. Huang, and Y. Xiang, "A secure cloud computing based framework for big data information management of smart grid, " IEEE Trans. Cloud Comput., vol. 3, no. 2, pp. 233-244, Apr./Jun. 2014.
32. M. Wen et al., "PaRQ: A privacy-preserving range query scheme over encrypted metering data for smart grid, " IEEE Trans. Emerg. Topics Comput., vol. 1, no. 1, pp. 178-191, Jun. 2013.
33. W. Hurst, M. Merabti, and P. Fergus, "Big data analysis techniques for cyber-Threat detection in critical infrastructures, " in Proc. 28th Int. Conf. Adv. Inf. Netw. Appl. Workshops (WAINA), Victoria, BC, Canada, 2014, pp. 916-921.
34. X. He et al., "A big data architecture design for smart grids based on random matrix theory, " IEEE Trans. Smart Grid, 2015, doi: 10.1109/TSG.2015.2445828.
35. S. Pan, T. Morris, and U. Adhikari, "Developing a hybrid intrusion detection system using data mining for power systems, " IEEE Trans. Smart Grid, vol. 6, no. 6, pp. 3104-3113, Nov. 2015.
36. C. C. O. Ramos, A. N. de Sousa, J. P. Papa, and A. X. Falcão, "A new approach for nontechnical losses detection based on optimumpath forest, " IEEE Trans. Power Syst., vol. 26, no. 1, pp. 181-189, Feb. 2011.
37. R. Mitchell and I.-R. Chen, "Behavior-rule based intrusion detection systems for safety critical smart grid applications, " IEEE Trans. Smart Grid, vol. 4, no. 3, pp. 1254-1263, Sep. 2013.
38. Z. Wang, F. Chen, and A. Xia, "Attribute-based online/offline encryption in smart grid, " in Proc. 24th Int. Conf. Comput. Commun. Netw. (ICCCN), Las Vegas, NV, USA, 2015, pp. 1-5.
39. C.-I. Fan, S.-Y. Huang, and Y.-L. Lai, "Privacy-enhanced data aggregation scheme against internal attackers in smart grid, " IEEE Trans. Ind. Informat., vol. 10, no. 1, pp. 666-675, Feb. 2014.
40. Z. Wan, G. Wang, Y. Yang, and S. Shi, "SKM: Scalable key management for advanced metering infrastructure in smart grids, " IEEE Trans. Ind. Electron., vol. 61, no. 12, pp. 7055-7066, Dec. 2014.
41. W. Jia, H. Zhu, Z. Cao, X. Dong, and C. Xiao, "Human-factor-Aware privacy-preserving aggregation in smart grid, " IEEE Syst. J., vol. 8, no. 2, pp. 598-607, Jun. 2014.
42. D. Wei, Y. Lu, M. Jafari, P. M. Skare, and K. Rohde, "Protecting smart grid automation systems against cyberattacks, " IEEE Trans. Smart Grid, vol. 2, no. 4, pp. 782-795, Dec. 2011.
43. X. Dong, J. Zhou, and Z. Cao, "Efficient privacy-preserving temporal and spacial data aggregation for smart grid communications, " Concurrency Comput. Pract. Exp., vol. 28, no. 4, pp. 1145-1160, 2016.
44. M. A. Rahman, E. Al-Shaer, and P. Bera, "A noninvasive threat analyzer for advanced metering infrastructure in smart grid, " IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 273-287, Mar. 2013.
45. Q. Li et al., "ESO: An efficient and secure outsourcing scheme for smart grid, " in Proc. Int. Conf. Wireless Commun. Signal Process. (WCSP), Hangzhou, China, 2013, pp. 1-6.
46. E. Gonzalez, L. B. Kish, R. S. Balog, and P. Enjeti, "Information theoretically secure, enhanced Johnson noise based key distribution over the smart grid with switched filters, " PLoS One, vol. 8, no. 7, 2013, Art. no. e70206.
47. H. Li et al., "EPPDR: An efficient privacy-preserving demand response scheme with adaptive key evolution in smart grid, " IEEE Trans. Parallel Distrib. Syst., vol. 25, no. 8, pp. 2053-2064, Aug. 2014.
48. X. Huang et al., "Cost-effective authentic and anonymous data sharing with forward security, " IEEE Trans. Comput., vol. 64, no. 4, pp. 971-983, Apr. 2015.
49. S. Ruj and A. Nayak, "A decentralized security framework for data aggregation and access control in smart grids, " IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 196-205, Mar. 2013.
50. M. M. E. A. Mahmoud, J. Misic, and X. Shen, "Efficient public-key certificate revocation schemes for smart grid, " in Proc. IEEE Glob. Commun. Conf. (GLOBECOM), Atlanta, GA, USA, 2013, pp. 778-783.
51. M. M. E. A. Mahmoud, J. Mišíc, K. Akkaya, and X. Shen, "Investigating public-key certificate revocation in smart grid, " IEEE Internet Things, vol. 2, no. 6, pp. 490-503, Dec. 2015.
52. M. M. E. A. Mahmoud, K. Akkaya, K. Rabieh, and S. Tonyali, "An efficient certificate revocation scheme for large-scale AMI networks, " in Proc. IEEE Int. Perform. Comput. Commun. Conf. (IPCCC), Austin, TX, USA, 2014, pp. 1-8.
53. X. Liang, X. Li, R. Lu, X. Lin, and X. Shen, "UDP: Usage-based dynamic pricing with privacy preservation for smart grid, " IEEE Trans. Smart Grid, vol. 4, no. 1, pp. 141-150, Mar. 2013.
54. Q. Zhang, L. Yang, and Z. Chen, "Privacy preserving deep computation model on cloud for big data feature learning, " IEEE Trans. Comput., vol. 65, no. 5, pp. 1351-1362, May 2015, doi: 10.1109/TC.2015.2470255.
55. M. Wen et al., "ECQ: An efficient conjunctive query scheme over encrypted multidimensional data in smart grid, " in Proc. IEEE Glob. Commun. Conf. (GLOBECOM), Atlanta, GA, USA, 2013, pp. 796-801.
56. Y. Yang, H. Li, M. Wen, H. Luo, and R. Lu, "Achieving ranked range query in smart grid auction market, " in Proc. IEEE Int. Conf. Commun. (ICC), Sydney, NSW, Australia, 2014, pp. 951-956.
57. D. Boneh and B. Waters, "Conjunctive, subset, and range queries on encrypted data, " in Theory of Cryptography. Heidelberg, Germany: Springer, 2007, pp. 535-554.
58. S. S. S. Rawat, V. A. Polavarapu, V. Kumar, E. Aruna, and V. Sumathi, "Anomaly detection in smart grid using rough set theory and K cross validation, " in Proc. Int. Conf. Circuit Power Comput. Technol. (ICCPCT), Nagercoil, India, 2014, pp. 479-483.
59. S. McLaughlin, D. Podkuiko, and P. McDaniel, "Energy theft in the advanced metering infrastructure, " in Critical Information Infrastructures Security. Heidelberg, Germany: Springer, 2010, pp. 176-187.
60. S. McLaughlin, B. Holbert, A.-Q. Fawaz, R. Berthier, and S. Zonouz, "A multi-sensor energy theft detection framework for advanced metering infrastructures, " IEEE J. Sel. Areas Commun., vol. 31, no. 7, pp. 1319-1330, Jul. 2013.
61. S. Amin, G. A. Schwartz, A. A. Cardenas, and S. S. Sastry, "Gametheoretic models of electricity theft detection in smart utility networks: Providing new capabilities with advanced metering infrastructure, " IEEE Control Syst., vol. 35, no. 1, pp. 66-81, Feb. 2015.
62. O. Kosut, L. Jia, R. J. Thomas, and L. Tong, "Malicious data attacks on the smart grid, " IEEE Trans. Smart Grid, vol. 2, no. 4, pp. 645-658, Dec. 2011.
63. A.-H. Mohsenian-Rad and A. Leon-Garcia, "Distributed Internet-based load altering attacks against smart power grids, " IEEE Trans. Smart Grid, vol. 2, no. 4, pp. 667-674, Dec. 2011.
64. Q. Yang et al., "On false data-injection attacks against power system state estimation: Modeling and countermeasures, " IEEE Trans. Parallel Distrib. Syst., vol. 25, no. 3, pp. 717-729, Mar. 2014.
65. Y. Liu, P. Ning, and M. K. Reiter, "False data injection attacks against state estimation in electric power grids, " ACM Trans. Inf. Syst. Security, vol. 14, no. 1, 2011, Art. no. 13.
66. O. Kosut, L. Jia, R. J. Thomas, and L. Tong, "Malicious data attacks on smart grid state estimation: Attack strategies and countermeasures, " in Proc. 1st IEEE Int. Conf. Smart Grid Commun. (SmartGridComm), Gaithersburg, MD, USA, 2010, pp. 220-225.
67. O. Kosut, L. Jia, R. J. Thomas, and L. Tong, "Malicious data attacks on the smart grid, " IEEE Trans. Smart Grid, vol. 2, no. 4, pp. 645-658, Dec. 2011.
68. S. Li, Y. Yilmaz, and X. Wang, "Quickest detection of false data injection attack in wide-Area smart grids, " IEEE Trans. Smart Grid, vol. 6, no. 6, pp. 2715-2735, Nov. 2015.
69. L. Liu, M. Esmalifalak, and Z. Han, "Detection of false data injection in power grid exploiting low rank and sparsity, " in Proc. IEEE Int. Conf. Commun. (ICC), Budapest, Hungary, 2013, pp. 4461-4465.
70. X. Yang et al., "A novel en-route filtering scheme against false data injection attacks in cyber-physical networked systems, " IEEE Trans. Comput., vol. 64, no. 1, pp. 4-18, Jan. 2015.
71. Y. W. Law, T. Alpcan, and M. Palaniswami, "Security games for risk minimization in automatic generation control, " IEEE Trans. Power Syst., vol. 30, no. 1, pp. 223-232, Jan. 2015.
72. W. Yu, D. Griffith, L. Ge, S. Bhattarai, and N. Golmie, "An integrated detection system against false data injection attacks in the smart grid, " Security Commun. Netw., vol. 8, no. 2, pp. 91-109, 2015.
73. M. Ozay, I. Esnaola, F. T. Vural, S. R. Kulkarni, and H. V. Poor, "Sparse attack construction and state estimation in the smart grid: Centralized and distributed models, " IEEE J. Sel. Areas Commun., vol. 31, no. 7, pp. 1306-1318, Jul. 2013.
74. S. Cui et al., "Coordinated data-injection attack and detection in the smart grid: A detailed look at enriching detection solutions, " IEEE Signal Process. Mag., vol. 29, no. 5, pp. 106-115, Sep. 2012.
75. Y. Yuan, Z. Li, and K. Ren, "Modeling load redistribution attacks in power systems, " IEEE Trans. Smart Grid, vol. 2, no. 2, pp. 382-390, Jun. 2011.
76. A. Ashok and M. Govindarasu, "Cyber attacks on power system state estimation through topology errors, " in Proc. IEEE Power Energy Soc. Gen. Meeting, San Diego, CA, USA, 2012, pp. 1-8.
77. O. Vukoviæ and G. Dán, "On the security of distributed power system state estimation under targeted attacks, " in Proc. 28th Annu. ACM Symp. Appl. Comput., Coimbra, Portugal, 2013, pp. 666-672.
78. A. Tajer, S. Kar, H. V. Poor, and S. Cui, "Distributed joint cyber attack detection and state recovery in smart grids, " in Proc. IEEE Int. Conf. Smart Grid Commun. (SmartGridComm), Brussels, Belgium, 2011, pp. 202-207.
79. L. Liu, Z. Han, H. V. Poor, and S. Cui, "Big data processing for smart grid security, " in Big Data Over Networks. Cambridge, U.K.: Cambridge Univ. Press, 2016, pp. 217-243.
80. J. Zhao, G. Zhang, Z. Y. Dong, and K. P. Wong, "Forecasting-Aided imperfect false data injection attacks against power system nonlinear state estimation, " IEEE Trans. Smart Grid, vol. 7, no. 1, pp. 6-8, Jan. 2016.
81. Y. Yamaguchi, A. Ogawa, A. Takeda, and S. Iwata, "Cyber security analysis of power networks by hypergraph cut algorithms, " IEEE Trans. Smart Grid, vol. 6, no. 5, pp. 2189-2199, Sep. 2015.
82. J. Kim, L. Tong, and R. J. Thomas, "Subspace methods for data attack on state estimation: A data driven approach, " IEEE Trans. Signal Process., vol. 63, no. 5, pp. 1102-1114, Mar. 2015.
83. J. Zhao et al., "Short-Term state forecasting-Aided method for detection of smart grid general false data injection attacks, " IEEE Trans. Smart Grid, vol. pp, issue 99, 2015, pp. 1-11, doi: 10.1109/TSG.2015.2492827.
84. F. Capitanescu et al., "State-of-The-Art, challenges, and future trends in security constrained optimal power flow, " Elect. Power Syst. Res., vol. 81, no. 8, pp. 1731-1741, 2011.
85. A. J. Ardakani and F. Bouffard, "Identification of umbrella constraints in DC-based security-constrained optimal power flow, " IEEE Trans. Power Syst., vol. 28, no. 4, pp. 3924-3934, Nov. 2013.
86. A. Teixeira, H. Sandberg, G. Dán, and K. H. Johansson, "Optimal power flow: Closing the loop over corrupted data, " in Proc. Amer. Control Conf. (ACC), Montréal, QC, Canada, 2012, pp. 3534-3540.
87. L. Jia, J. Kim, R. J. Thomas, and L. Tong, "Impact of data quality on real-Time locational marginal price, " IEEE Trans. Power Syst., vol. 29, no. 2, pp. 627-636, Mar. 2014.
88. L. Platbrood, F. Capitanescu, C. Merckx, H. Crisciu, and L. Wehenkel, "A generic approach for solving nonlinear-discrete security-constrained optimal power flow problems in large-scale systems, " IEEE Trans. Power Syst., vol. 29, no. 3, pp. 1194-1203, May 2014.