http://iet.metastore.ingenta.com
1887

access icon openaccess Detection of false data injection attacks against state estimation in smart grids based on a mixture Gaussian distribution learning method

  • PDF
    4.542960166931152MB
  • XML
    201.9482421875Kb
  • HTML
    235.5751953125Kb
Loading full text...

Full text loading...

/deliver/fulltext/iet-cps/2/4/IET-CPS.2017.0013.html;jsessionid=2e1oy0itxy7kt.x-iet-live-01?itemId=%2fcontent%2fjournals%2f10.1049%2fiet-cps.2017.0013&mimeType=html&fmt=ahah

References

    1. 1)
      • Z. Zhan , M. Xu , S. Xu .
        1. Zhan, Z., Xu, M., Xu, S.: ‘Characterizing honeypot-captured cyber attacks: statistical framework and case study’, IEEE Trans. Inf. Forensics Sec., 2013, 8, pp. 17751789.
        . IEEE Trans. Inf. Forensics Sec. , 1775 - 1789
    2. 2)
      • Y. Yan , Y. Qian , H. Sharif .
        2. Yan, Y., Qian, Y., Sharif, H., et al: ‘A survey on cyber security for smart grid communications’, IEEE Commun. Surv. Tutor., 2012, 14, pp. 9981010.
        . IEEE Commun. Surv. Tutor. , 998 - 1010
    3. 3)
      • W. Wang , Z. Lu .
        3. Wang, W., Lu, Z.: ‘Cyber security in the smart grid: survey and challenges’, Comput. Netw., 2013, 57, pp. 13441371.
        . Comput. Netw. , 1344 - 1371
    4. 4)
      • G.N. Ericsson .
        4. Ericsson, G.N.: ‘Cyber security and power system communication—essential parts of a smart grid infrastructure’, IEEE Trans. Power Deliv., 2010, 25, pp. 15011507.
        . IEEE Trans. Power Deliv. , 1501 - 1507
    5. 5)
      • Y. Liu , P. Ning , M.K. Reiter .
        5. Liu, Y., Ning, P., Reiter, M.K.: ‘False data injection attacks against state estimation in electric power grids’, ACM Trans. Inf. Syst. Secur., 2011, 14, p. 13.
        . ACM Trans. Inf. Syst. Secur. , 13
    6. 6)
      • M. Cheniae , L. Mili , P. Rousseeuw .
        6. Cheniae, M., Mili, L., Rousseeuw, P.: ‘Identification of multiple interacting bad data via power system decomposition’, IEEE Trans. Power Syst., 1996, 11, pp. 15551563.
        . IEEE Trans. Power Syst. , 1555 - 1563
    7. 7)
      • Y. Huang , M. Esmalifalak , H. Nguyen .
        7. Huang, Y., Esmalifalak, M., Nguyen, H., et al: ‘Bad data injection in smart grid: attack and defense mechanisms’, IEEE Commun. Mag., 2013, 51, pp. 2733.
        . IEEE Commun. Mag. , 27 - 33
    8. 8)
      • G. Liang , J. Zhao , F. Luo .
        8. Liang, G., Zhao, J., Luo, F., et al: ‘A review of false data injection attacks against modern power systems’, IEEE Trans. Smart Grid, 2017, 8, (4), pp. 16301638.
        . IEEE Trans. Smart Grid , 4 , 1630 - 1638
    9. 9)
      • H. He , J. Yan .
        9. He, H., Yan, J.: ‘Cyber-physical attacks and defences in the smart grid: a survey’, IET Cyber-Physical Syst. Theory Appl., 2016, 1, pp. 1327.
        . IET Cyber-Physical Syst. Theory Appl. , 13 - 27
    10. 10)
      • S. Li , Y. Yılmaz , X. Wang .
        10. Li, S., Yılmaz, Y., Wang, X.: ‘Quickest detection of false data injection attack in wide-area smart grids’, IEEE Trans. Smart Grid, 2015, 6, pp. 27252735.
        . IEEE Trans. Smart Grid , 2725 - 2735
    11. 11)
      • L. Liu , M. Esmalifalak , Q. Ding .
        11. Liu, L., Esmalifalak, M., Ding, Q., et al: ‘Detecting false data injection attacks on power grid by sparse optimization’, IEEE Trans. Smart Grid, 2014, 5, pp. 612621.
        . IEEE Trans. Smart Grid , 612 - 621
    12. 12)
      • K. Manandhar , X. Cao , F. Hu .
        12. Manandhar, K., Cao, X., Hu, F., et al: ‘Detection of faults and attacks including false data injection attack in smart grid using kalman filter’, IEEE Trans. Control Netw. Syst., 2014, 1, pp. 370379.
        . IEEE Trans. Control Netw. Syst. , 370 - 379
    13. 13)
      • H. Sedghi , E. Jonckheere .
        13. Sedghi, H., Jonckheere, E.: ‘Statistical structure learning to ensure data integrity in smart grid’, IEEE Trans. Smart Grid, 2015, 6, pp. 19241933.
        . IEEE Trans. Smart Grid , 1924 - 1933
    14. 14)
      • F. Ahmadloo , F.R. Salmasi .
        14. Ahmadloo, F., Salmasi, F.R.: ‘A cyber-attack on communication link in distributed systems and detection scheme based on H-infinity filtering’. 2017 IEEE Int. Conf. Industrial Technology (ICIT), Toronto, ON, 2017, pp. 698703.
        . 2017 IEEE Int. Conf. Industrial Technology (ICIT) , 698 - 703
    15. 15)
      • J. Qi , A. Hahn , X. Lu .
        15. Qi, J., Hahn, A., Lu, X., et al: ‘Cybersecurity for distributed energy resources and smart inverters’, IET Cyber Physical Syst. Theory Appl., 2016, 1, pp. 2839.
        . IET Cyber Physical Syst. Theory Appl. , 28 - 39
    16. 16)
      • Z. Li , D. Jin , C. Hannon .
        16. Li, Z., Jin, D., Hannon, C., et al: ‘Assessing and mitigating cybersecurity risks of traffic light systems in smart cities’, IET Cyber-Physical Syst. Theory Appl., 2016, 1, pp. 6069.
        . IET Cyber-Physical Syst. Theory Appl. , 60 - 69
    17. 17)
      • Z.-H. Yu , W.-L. Chin .
        17. Yu, Z.-H., Chin, W.-L.: ‘Blind false data injection attack using pca approximation method in smart grid’, IEEE Trans. Smart Grid, 2015, 6, pp. 12191226.
        . IEEE Trans. Smart Grid , 1219 - 1226
    18. 18)
      • X. Liu , Z. Li .
        18. Liu, X., Li, Z.: ‘Local load redistribution attacks in power systems with incomplete network information’, IEEE Trans. Smart Grid, 2014, 5, pp. 16651676.
        . IEEE Trans. Smart Grid , 1665 - 1676
    19. 19)
      • X. Liu , Z. Bao , D. Lu .
        19. Liu, X., Bao, Z., Lu, D., et al: ‘Modeling of local false data injection attacks with reduced network information’, IEEE Trans. Smart Grid, 2015, 6, pp. 16861696.
        . IEEE Trans. Smart Grid , 1686 - 1696
    20. 20)
      • M. Ozay , I. Esnaola , F.T.Y. Vural .
        20. Ozay, M., Esnaola, I., Vural, F.T.Y., et al: ‘Distributed models for sparse attack construction and state vector estimation in the smart grid’. 2012 IEEE Third Int. Conf. Smart Grid Communications (SmartGridComm), 2012, pp. 306311.
        . 2012 IEEE Third Int. Conf. Smart Grid Communications (SmartGridComm) , 306 - 311
    21. 21)
      • H. Huang , Q. Yan , Y. Zhao .
        21. Huang, H., Yan, Q., Zhao, Y., et al: ‘False data separation for data security in smart grids’, Knowl. Inf. Syst., 2017, 52, (3), pp. 815834.
        . Knowl. Inf. Syst. , 3 , 815 - 834
    22. 22)
      • Q. Yang , J. Yang , W. Yu .
        22. Yang, Q., Yang, J., Yu, W., et al: ‘On false data-injection attacks against power system state estimation: modeling and countermeasures’, IEEE Trans. Parallel Distrib. Syst., 2014, 25, pp. 717729.
        . IEEE Trans. Parallel Distrib. Syst. , 717 - 729
    23. 23)
      • R.B. Bobba , K.M. Rogers , Q. Wang .
        23. Bobba, R.B., Rogers, K.M., Wang, Q., et al: ‘Detecting false data injection attacks on dc state estimation’. Preprints of the First Workshop on Secure Control Systems, CPSWEEK, 2010.
        . Preprints of the First Workshop on Secure Control Systems, CPSWEEK
    24. 24)
      • S. Bi , Y.J. Zhang .
        24. Bi, S., Zhang, Y.J.: ‘Graphical methods for defense against false-data injection attacks on power system state estimation’, IEEE Trans. Smart Grid, 2014, 5, pp. 12161227.
        . IEEE Trans. Smart Grid , 1216 - 1227
    25. 25)
      • E.J. Candès , X. Li , Y. Ma .
        25. Candès, E.J., Li, X., Ma, Y., et al: ‘Robust principal component analysis?’, J. ACM, 2011, 58, p. 11.
        . J. ACM , 11
    26. 26)
      • Z.M. Fadlullah , M.M. Fouda , N. Kato .
        26. Fadlullah, Z.M., Fouda, M.M., Kato, N., et al: ‘An early warning system against malicious activities for smart grid communications’, IEEE Netw., 2011, 25, pp. 5055.
        . IEEE Netw. , 50 - 55
    27. 27)
      • Y. Zhang , L. Wang , W. Sun .
        27. Zhang, Y., Wang, L., Sun, W., et al: ‘Distributed intrusion detection system in a multi-layer network architecture of smart grids’, IEEE Trans. Smart Grid, 2011, 2, pp. 796808.
        . IEEE Trans. Smart Grid , 796 - 808
    28. 28)
      • R.C.B. Hink , J.M. Beaver , M.A. Buckner .
        28. Hink, R.C.B., Beaver, J.M., Buckner, M.A., et al: ‘Machine learning for power system disturbance and cyber-attack discrimination’. 2014 7th Int. Symp. Resilient Control Systems (ISRCS), 2014, pp. 18.
        . 2014 7th Int. Symp. Resilient Control Systems (ISRCS) , 1 - 8
    29. 29)
      • J. Yan , H. He , X. Zhong .
        29. Yan, J., He, H., Zhong, X., et al: ‘Q-learning based vulnerability analysis of smart grid against sequential topology attacks’, IEEE Trans. Inf. Forensics Sec., 2017, 12, (1), pp. 200210.
        . IEEE Trans. Inf. Forensics Sec. , 1 , 200 - 210
    30. 30)
      • M. Ozay , I. Esnaola , F.T.Y. Vural .
        30. Ozay, M., Esnaola, I., Vural, F.T.Y., et al: ‘Machine learning methods for attack detection in the smart grid’, IEEE Trans. Neural Netw. Learn. Syst., 2016, 27, pp. 17731786.
        . IEEE Trans. Neural Netw. Learn. Syst. , 1773 - 1786
    31. 31)
      • J. Yan , B. Tang , H. He .
        31. Yan, J., Tang, B., He, H.: ‘Detection of false data attacks in smart grid with supervised learning’. 2016 Int. Joint Conf. Neural Networks (IJCNN), 2016, pp. 13951402.
        . 2016 Int. Joint Conf. Neural Networks (IJCNN) , 1395 - 1402
    32. 32)
      • O. Kosut , L. Jia , R.J. Thomas .
        32. Kosut, O., Jia, L., Thomas, R.J., et al: ‘Malicious data attacks on the smart grid’, IEEE Trans. Smart Grid, 2011, 2, pp. 645658.
        . IEEE Trans. Smart Grid , 645 - 658
    33. 33)
      • J.M. Hendrickx , K.H. Johansson , R.M. Jungers .
        33. Hendrickx, J.M., Johansson, K.H., Jungers, R.M., et al: ‘Efficient computations of a security index for false data attacks in power networks’, IEEE Trans. Autom. Control, 2014, 59, pp. 31943208.
        . IEEE Trans. Autom. Control , 3194 - 3208
    34. 34)
      • R.D. Zimmerman , C.E. Murillo-Sánchez , R.J. Thomas .
        34. Zimmerman, R.D., Murillo-Sánchez, C.E., Thomas, R.J.: ‘MATPOWER: Steady-state operations, planning, and analysis tools for power systems research and education’, IEEE Trans. Power Syst., 2011, 26, pp. 1219.
        . IEEE Trans. Power Syst. , 12 - 19
    35. 35)
      • J.J. Grainger , W.D. Stevenson . (1994)
        35. Grainger, J.J., Stevenson, W.D.: ‘Power system analysis’ (McGraw-Hill, 1994).
        .
    36. 36)
      • A.J. Wood , B.F. Wollenberg . (2012)
        36. Wood, A.J., Wollenberg, B.F.: ‘Power generation, operation, and control’ (John Wiley & Sons, 2012).
        .
    37. 37)
      • F. Schweppe .
        37. Schweppe, F.: ‘Power system state estimation, parts I, II and III’, IEEE Trans. Power Apparatus Syst., 1970, 89, pp. 120135.
        . IEEE Trans. Power Apparatus Syst. , 120 - 135
    38. 38)
      • N. Cristianini , J. Shawe-Taylor . (2000)
        38. Cristianini, N., Shawe-Taylor, J.: ‘An introduction to support vector machines and other kernel-based learning methods’ (Cambridge University Press, 2000).
        .
    39. 39)
      • I. Steinwart , A. Christmann . (2008)
        39. Steinwart, I., Christmann, A.: ‘Support vector machines’ (Springer Science & Business Media, 2008).
        .
    40. 40)
      • C.K. Williams , C.E. Rasmussen . (2006)
        40. Williams, C.K., Rasmussen, C.E.: ‘Smoothing, weight functions and equivalent kernels’, in (Eds): ‘Gaussian processes for machine learning’ (The MIT Press, Cambridge, 2006), pp. 2426.
        .
    41. 41)
      • S. Kulkarni , G. Harman . (2011)
        41. Kulkarni, S., Harman, G.: ‘An elementary introduction to statistical learning theory’ (John Wiley & Sons, 2011), vol. 853.
        .
    42. 42)
      • M. Kuusela , T. Vatanen , E. Malmi .
        42. Kuusela, M., Vatanen, T., Malmi, E., et al: ‘Semi-supervised anomaly detection-towards model-independent searches of new physics’. J. Phys. Conf. Ser., 2012, p. 012032.
        . J. Phys. Conf. Ser. , 012032
    43. 43)
      • V. Chandola , A. Banerjee , V. Kumar .
        43. Chandola, V., Banerjee, A., Kumar, V.: ‘Anomaly detection: a survey’, ACM computing surveys (CSUR), 2009, 41, p. 15.
        . ACM computing surveys (CSUR) , 15
    44. 44)
      • G. McLachlan , D. Peel . (2004)
        44. McLachlan, G., Peel, D.: ‘Finite mixture models’ (John Wiley & Sons, 2004).
        .
    45. 45)
      • I.G. Costa Filho .
        45. Costa Filho, I.G.: ‘Mixture models for the analysis of gene expression: integration of multiple experiments and cluster validation’, Citeseer, 2008.
        . Citeseer
    46. 46)
      • L. Bottou , C.-J. Lin . (2007)
        46. Bottou, L., Lin, C.-J.: ‘Support vector machine solvers’, in Bottou, L., Chapelle, O., DeCoste, D., et al (Ed.), ‘Large Scale Kernel Machines’ (MIT Press, 2007), pp. 301320.
        .
    47. 47)
      • A. Bordes , S. Ertekin , J. Weston .
        47. Bordes, A., Ertekin, S., Weston, J., et al: ‘Fast kernel classifiers with online and active learning’, J. Mach. Learn. Res., 2005, 6, pp. 15791619.
        . J. Mach. Learn. Res. , 1579 - 1619
    48. 48)
      • Y. Weng , R. Negi , C. Faloutsos .
        48. Weng, Y., Negi, R., Faloutsos, C., et al: ‘Robust data-driven state estimation for smart grid’, IEEE Trans. Smart Grid, 2017, 8, (4), pp. 19561967.
        . IEEE Trans. Smart Grid , 4 , 1956 - 1967
    49. 49)
      • N. Chinchor , B. Sundheim .
        49. Chinchor, N., Sundheim, B.: ‘MUC-5 evaluation metrics’. Proc. 5th Conf. Message Understanding, 1993, pp. 6978.
        . Proc. 5th Conf. Message Understanding , 69 - 78
    50. 50)
      • M. Aitkin , D. Vu , B. Francis .
        50. Aitkin, M., Vu, D., Francis, B.: ‘A new bayesian approach for determining the number of components in a finite mixture’, Metron, 2015, 73, pp. 155176.
        . Metron , 155 - 176
    51. 51)
      • F. Salmasi .
        51. Salmasi, F.: ‘A self-healing induction motor drive with model free sensor tampering and sensor fault detection, isolation, and compensation’, IEEE Trans. Ind. Electron., 2017, 8, (64), pp. 61056115.
        . IEEE Trans. Ind. Electron. , 64 , 6105 - 6115
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-cps.2017.0013
Loading

Related content

content/journals/10.1049/iet-cps.2017.0013
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address