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Detection and Prevention of False Data Injection Attacks in the Measurement Infrastructure of Smart Grids

Author

Listed:
  • Muhammad Awais Shahid

    (Department of Electrical & Computer Engineering, Air University, Islamabad 44230, Pakistan)

  • Fiaz Ahmad

    (Department of Electrical & Computer Engineering, Air University, Islamabad 44230, Pakistan)

  • Fahad R. Albogamy

    (Computer Sciences Program, Turabah University College, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia)

  • Ghulam Hafeez

    (Department of Electrical Engineering, University of Engineering and Technology, Mardan 23200, Pakistan)

  • Zahid Ullah

    (Department of Electrical Engineering, University of Management and Technology Lahore, Sialkot Campus, Sialkot 51310, Pakistan)

Abstract

The smart grid has become a cyber-physical system and the more cyber it becomes, the more prone it is to cyber-attacks. One of the most important cyber-attacks in smart grids is false data injection (FDI) into its measurement infrastructure. This attack could manipulate the control center in a way to execute wrong control actions on various generating units, causing system instabilities that could ultimately lead to power system blackouts. In this study, a novel false data detection and prevention paradigm was proposed for the measurement infrastructure in smart grids. Two techniques were devised to manage cyber-attacks, namely, the fixed dummy value model and the variable dummy value model. Limitations of the fixed dummy value model were identified and addressed in the variable dummy value model. Both methods were tested on an IEEE 14 bus system and it was shown through the results that an FDI attack that easily bypassed the bad data filter of the state estimator was successfully identified by the fixed dummy model. Second, attacks that were overlooked by the fixed dummy model were identified by the variable dummy method. In this way, the power system was protected from FDI attacks.

Suggested Citation

  • Muhammad Awais Shahid & Fiaz Ahmad & Fahad R. Albogamy & Ghulam Hafeez & Zahid Ullah, 2022. "Detection and Prevention of False Data Injection Attacks in the Measurement Infrastructure of Smart Grids," Sustainability, MDPI, vol. 14(11), pages 1-25, May.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:11:p:6407-:d:822760
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    References listed on IDEAS

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    1. Muhammad Awais Shahid & Fiaz Ahmad & Rehan Nawaz & Saad Ullah Khan & Abdul Wadood & Hani Albalawi, 2023. "A Novel False Measurement Data Detection Mechanism for Smart Grids," Energies, MDPI, vol. 16(18), pages 1-17, September.

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