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End-User Privacy Protection Scheme from cyber intrusion in smart grid advanced metering infrastructure

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  • Singh, Neeraj Kumar
  • Mahajan, Vasundhara

Abstract

Smart monitoring work as a backbone of a smart grid distribution network. To support the existing grid toward a smart grid scenario, smart metering plays a vital role at the customer end side. The massive deployment of smart meters in the distribution side raises a concern about data loss, privacy loss and False Data Intrusion Attack (FDIA). In order to protect the commercial and non-commercial users “End-User Privacy Protection Scheme (EPPS)” is proposed, which allows smart meters to report correct reading during FDIA/intrusion. In this proposed technique statistical machine learning method based on Gaussian Mixture Model Clustering (GMMC) and Mean Square Error (MSE) using two performance indices, the Data Protection Capability (DPC) and the confidential interval for true measurement against false data injection is evaluated. For performance evaluation of the proposed methodology, a passive distributed network is studied. Using EPPS, customer pattern is reconstructed by eliminating cyber intrusion due to FDIA on a smart metering system. This research validates the proposed method through MATLAB software using the smart meter data taken from the National Renewable Energy Laboratory (NREL).

Suggested Citation

  • Singh, Neeraj Kumar & Mahajan, Vasundhara, 2021. "End-User Privacy Protection Scheme from cyber intrusion in smart grid advanced metering infrastructure," International Journal of Critical Infrastructure Protection, Elsevier, vol. 34(C).
    • Handle: RePEc:eee:ijocip:v:34:y:2021:i:c:s1874548221000020
    DOI: 10.1016/j.ijcip.2021.100410
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    References listed on IDEAS

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    1. Ahmad Alomari, 2013. "Implementing Rsa Algorithm For Fully Distributed Certificate Authority In Manet," Romanian Economic Business Review, Romanian-American University, vol. 7(1), pages 176-183, May.
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    Cited by:

    1. Michał Krzykowski, 2021. "Legal Aspects of Cybersecurity in the Energy Sector—Current State and Latest Proposals of Legislative Changes by the EU," Energies, MDPI, vol. 14(23), pages 1-14, November.
    2. Jena, Prasanta Kumar & Ghosh, Subhojit & Koley, Ebha, 2021. "Design of a coordinated cyber-physical attack in IoT based smart grid under limited intruder accessibility," International Journal of Critical Infrastructure Protection, Elsevier, vol. 35(C).
    3. Taimoor Ahmad Khan & Amjad Ullah & Ghulam Hafeez & Imran Khan & Sadia Murawwat & Faheem Ali & Sajjad Ali & Sheraz Khan & Khalid Rehman, 2022. "A Fractional Order Super Twisting Sliding Mode Controller for Energy Management in Smart Microgrid Using Dynamic Pricing Approach," Energies, MDPI, vol. 15(23), pages 1-14, November.
    4. 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).

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