Your browser does not support JavaScript!
http://iet.metastore.ingenta.com
1887

access icon openaccess GPS spoofing-based time synchronisation attack in advanced metering infrastructure and its protection

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Received 04/02/2020, Accepted 03/06/2020, Revised 21/04/2020, Published 15/06/2020

Advanced metering infrastructure (AMI) plays a key role in power systems. Since smart meters and meter collectors are synchronised to the time synchronisation devices (TSDs) in the head end system (HES) of AMI, they are vulnerable to global positioning system (GPS) spoofing-based time synchronisation attack (TSA). Impacts of GPS spoofing-based TSA on AMI are investigated in this study. It is uncovered that, since AMI is a distributed networked system and metering data and control commands transmitted in AMI could be of large latency, data and commands with large latency over the specific threshold are considered to be invalid according to validity verification mechanism of average distributed system. Therefore, the disorder in time synchronisation induced by GPS spoofing-based TSA could disable functions of HES of AMI, such as meter reading and remote control. A time jitter detection-based approach is developed to identify and prevent from GPS spoofing-based TSA. A high-precision oven-controlled crystal oscillator with cumulative error compensation is utilised to identify time jitter of the satellite clock and help ride through sustained GPS spoofing-based TSA. Simulation on FPGA demonstrates the effectiveness of the proposed approach.

Inspec keywords: field programmable gate arrays; synchronisation; metering; smart meters; Global Positioning System; error compensation; timing jitter; crystal oscillators

Other keywords: Global Positioning System spoofing-based time synchronisation attack; cumulative error compensation; power systems; FPGA; validity verification mechanism; meter collectors; time synchronisation devices; smart meters; satellite clock; advanced metering infrastructure; time jitter detection-based approach; meter reading; head end system; metering data; AMI; distributed networked system; GPS spoofing-based time synchronisation attack; average distributed system; high-precision oven-controlled crystal oscillator; sustained GPS spoofing-based TSA

Subjects: Radionavigation and direction finding; Power system measurement and metering; Logic circuits; Oscillators; Display, recording and indicating instruments

References

    1. 1)
      • 19. Chun, S.-H., Chen, R., Xiang, B.-W.: ‘Frequency correction method of OCXO and its application in the data acquisition of electrical prospecting’, WSEAS Trans. Circuits Syst., 2015, 14, pp. 68–81.
    2. 2)
      • 7. Bhatti, J., Humphreys, T.E.: ‘Hostile control of ships via false GPS signals: demonstration and detection’, J. Inst. Navig., 2017, 64, (1), pp. 51–66.
    3. 3)
      • 14. Rivera, E., Baykov, R., Gu, G.: ‘A study on unmanned vehicles and cyber security’, J. Def. Model. Simul.: Appl., Methodol., Technol., 2015, 12, (4), pp. 1–7.
    4. 4)
      • 16. Montgomery, P.Y., Humphreys, T.E., Ledvina, B.M.: ‘Receiver-autonomous spoofing detection: experimental results of a multi-antenna receiver defense against a portable civil GPS spoofer’. Proc. of the Institute of Navigation, National Technical Meeting, Anaheim, CA, USA., 2009, vol. 1, pp. 124–130.
    5. 5)
      • 20. Milaat, F.A., Liu, H.: ‘Decentralized detection of GPS spoofing in vehicular ad hoc networks’, IEEE Commun. Lett., 2018, 22, (6), pp. 1256–1259.
    6. 6)
      • 11. Fan, Y., Zhang, Z., Trinkle, M., et al: ‘A cross-layer defense mechanism against GPS spoofing attacks on PMUs in smart grids’, IEEE Trans. Smart Grid, 2015, 6, (6), pp. 2659–2668.
    7. 7)
      • 4. Teng, J.-H., Chao, C.-W., Liu, B.-H., et al: ‘Communication performance assessment for advanced metering infrastructure’, Energies, 2018, 12, (1), p. 88.
    8. 8)
      • 21. Li, Y., Lu, C., Wang, Y., et al: ‘High-precision synchronous clock algorithm based on Kalman filtering and neural network’, Power Syst. Technol., 2019, 43, (3), pp. 777–784.
    9. 9)
      • 13. Huang, L., Yang, Q.: ‘Low cost GPS simulator: GPS spoofing by SDR’, 2015DEF CON 23.
    10. 10)
      • 6. He, H., Yan, J..: ‘Cyber-physical attacks and defence in the smart grid: a survey’, IET Cyber-Phys. Syst.: Theory Appl., 2016, 1, (1), pp. 13–27.
    11. 11)
      • 1. Gungor, V.C., Sahin, D, Kocak, T., et al: ‘Smart grid technologies: communication technologies and standards’, IEEE Trans. Ind. Inf., 2011, 7, (4), pp. 529–539.
    12. 12)
      • 8. Konstantinou, C., Sazos, M., Musleh, A.S., et al: ‘GPS spoofing effect on phase angle monitoring and control in a real-time digital simulator-based hardware-in-the-loop environment’, IET Cyber-Phys. Syst., Theory Appl., 2017, 2, (4), pp. 180–187.
    13. 13)
      • 12. Humphreys, T.E., Ledvina, B.M., Psiaki, M.L., et al: ‘Assessing the spoofing threat: development of a portable gps civilian spoofer’. Proc. of the ION GNSS Int. Technical Meeting of the Satellite Division, Savanna, CA, USA., 2008, vol. 55, p. 56.
    14. 14)
      • 9. Wang, Y., Hespanha, J.P.: ‘Distributed estimation of power system oscillation modes under attacks on GPS clocks’, IEEE Trans. Instrum. Meas., 2018, 67, (7), pp. 1626–1637.
    15. 15)
      • 17. Levin, P., De Lorenzo, D., Enge, P., et al: ‘Authenticating a signal based on an unknown component thereof’. U.S. Patent No. 7,969,354 B2, June 2011.
    16. 16)
      • 18. Liu, N., Chen, J., Zhu, L., et al: ‘A key management scheme for secure communications of advanced metering infrastructure in smart grid’, IEEE Trans. Ind. Electron., 2013, 60, (10), pp. 4746–4756.
    17. 17)
      • 5. Keemink, S., Roos, B.: ‘Security analysis of Dutch smart metering systems’ (University van Amsterdam, Amsterdam, the Netherlands, 2008).
    18. 18)
      • 2. Huang, X., Hu, T., Ye, C., et al: ‘Green-RPL: electric load data compression and classification based on deep stacked auto-encoders’, Energies, 2019, 12, (4), p. 653.
    19. 19)
      • 10. Zhang, Z., Gong, S., Dimitrovski, A.D., et al: ‘Time synchronization attack in smart grid: impact and analysis’, IEEE Trans. Smart Grid, 2013, 4, (1), pp. 87–98.
    20. 20)
      • 3. Halifax Regional Water Commission: ‘AMI technology assessment & feasibility study consolidated report’, 2014Available at: https://www.halifax.ca/sites/default/files/documents/home-property/water/AMITechnology-FianlReport.pdf.
    21. 21)
      • 15. ‘IEEE Std, IEEE standard for synchrophasor measurements for power systems, C37.118.1-2011 (revision of IEEE Std C37.118-2005)’, 2011.
http://iet.metastore.ingenta.com/content/journals/10.1049/joe.2020.0022
Loading

Related content

content/journals/10.1049/joe.2020.0022
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
Print this page
This is a required field
Please enter a valid email address