IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i15p3862-d391131.html
   My bibliography  Save this article

Cost-Effective Placement of Phasor Measurement Units to Defend against False Data Injection Attacks on Power Grid

Author

Listed:
  • Junhyung Bae

    (School of Electronic and Electrical Engineering, Daegu Catholic University, 13-13 Hayang-ro, Hayang-eup, Gyeongsan-si, Gyeongbuk 38430, Korea)

Abstract

This study presents the phasor measurement unit (PMU) placement strategy in the presence of false data injection attacks which is one of the most serious security threats against power grid. It is focused on applications related to supervisory control and data acquisition (SCADA) systems where measurement data can be easily corrupted by adversaries without getting caught by the system. To safeguard power grids against malicious attacks, procedures have been proposed to facilitate the placement of secure PMUs to defend against false data injection attacks in a highly cost-effective way. It has formulated a method of identifying measurements that are vulnerable to false data injection attacks. It was discovered that a weak power grid can be transformed into a robust power grid by adding a few PMUs at vulnerable locations. Simulations on the IEEE standard test systems demonstrate the benefits of the proposed procedure.

Suggested Citation

  • Junhyung Bae, 2020. "Cost-Effective Placement of Phasor Measurement Units to Defend against False Data Injection Attacks on Power Grid," Energies, MDPI, vol. 13(15), pages 1-15, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3862-:d:391131
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/15/3862/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/15/3862/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mehdi Ganjkhani & Seyedeh Narjes Fallah & Sobhan Badakhshan & Shahaboddin Shamshirband & Kwok-wing Chau, 2019. "A Novel Detection Algorithm to Identify False Data Injection Attacks on Power System State Estimation," Energies, MDPI, vol. 12(11), pages 1-19, June.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Muhammad Musadiq Ahmed & Muhammad Amjad & Muhammad Ali Qureshi & Kashif Imran & Zunaib Maqsood Haider & Muhammad Omer Khan, 2022. "A Critical Review of State-of-the-Art Optimal PMU Placement Techniques," Energies, MDPI, vol. 15(6), pages 1-25, March.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Meng Xia & Dajun Du & Minrui Fei & Xue Li & Taicheng Yang, 2020. "A Novel Sparse Attack Vector Construction Method for False Data Injection in Smart Grids," Energies, MDPI, vol. 13(11), pages 1-19, June.
    2. Shruti & Shalli Rani & Aman Singh & Reem Alkanhel & Dina S. M. Hassan, 2023. "SDAFA: Secure Data Aggregation in Fog-Assisted Smart Grid Environment," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
    3. Austin Cooper & Arturo Bretas & Sean Meyn, 2023. "Anomaly Detection in Power System State Estimation: Review and New Directions," Energies, MDPI, vol. 16(18), pages 1-15, September.
    4. Virginia M. Romero & Eduardo B. Fernandez, 2023. "Towards a Reference Architecture for Cargo Ports," Future Internet, MDPI, vol. 15(4), pages 1-32, April.
    5. Derya Betul Unsal & Taha Selim Ustun & S. M. Suhail Hussain & Ahmet Onen, 2021. "Enhancing Cybersecurity in Smart Grids: False Data Injection and Its Mitigation," Energies, MDPI, vol. 14(9), pages 1-36, May.
    6. Bitirgen, Kübra & Filik, Ümmühan Başaran, 2023. "A hybrid deep learning model for discrimination of physical disturbance and cyber-attack detection in smart grid," International Journal of Critical Infrastructure Protection, Elsevier, vol. 40(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3862-:d:391131. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.