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A Survey on Key Management and Authentication Approaches in Smart Metering Systems

Author

Listed:
  • Mohamed S. Abdalzaher

    (Department of Seismology, National Research Institute of Astronomy and Geophysics, Cairo 11421, Egypt)

  • Mostafa M. Fouda

    (Department of Electrical and Computer Engineering, College of Science and Engineering, Idaho State University, Pocatello, ID 83209, USA)

  • Ahmed Emran

    (Department of Electrical Engineering, Al-Azhar University, Cairo 11651, Egypt)

  • Zubair Md Fadlullah

    (Department of Computer Science, Western University, London, ON N6A 5B7, Canada)

  • Mohamed I. Ibrahem

    (Department of Cyber Security Engineering, George Mason University, Fairfax, VA 22030, USA
    Department of Electrical Engineering, Faculty of Engineering at Shoubra, Benha University, Cairo 11672, Egypt)

Abstract

The implementation of the smart grid (SG) and cyber-physical systems (CPS) greatly enhances the safety, reliability, and efficiency of energy production and distribution. Smart grids rely on smart meters (SMs) in converting the power grids (PGs) in a smart and reliable way. However, the proper operation of these systems needs to protect them against attack attempts and unauthorized entities. In this regard, key-management and authentication mechanisms can play a significant role. In this paper, we shed light on the importance of these mechanisms, clarifying the main efforts presented in the context of the literature. First, we address the main intelligent attacks affecting the SGs. Secondly, the main terms of cryptography are addressed. Thirdly, we summarize the common proposed key-management techniques with a suitable critique showing their pros and cons. Fourth, we introduce the effective paradigms of authentication in the state of the art. Fifth, the common two tools for verifying the security and integrity of protocols are presented. Sixth, the relevant research challenges are addressed to achieve trusted smart grids and protect their SMs against attack manipulations and unauthorized entities with a future vision. Accordingly, this survey can facilitate the efforts exerted by interested researchers in this regard.

Suggested Citation

  • Mohamed S. Abdalzaher & Mostafa M. Fouda & Ahmed Emran & Zubair Md Fadlullah & Mohamed I. Ibrahem, 2023. "A Survey on Key Management and Authentication Approaches in Smart Metering Systems," Energies, MDPI, vol. 16(5), pages 1-27, March.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2355-:d:1084476
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    References listed on IDEAS

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    1. Omar Hamdy & Hanan Gaber & Mohamed S. Abdalzaher & Mahmoud Elhadidy, 2022. "Identifying Exposure of Urban Area to Certain Seismic Hazard Using Machine Learning and GIS: A Case Study of Greater Cairo," Sustainability, MDPI, vol. 14(17), pages 1-24, August.
    2. Rosario Miceli, 2013. "Energy Management and Smart Grids," Energies, MDPI, vol. 6(4), pages 1-29, April.
    3. Denise Tellbach & Yan-Fu Li, 2018. "Cyber-Attacks on Smart Meters in Household Nanogrid: Modeling, Simulation and Analysis," Energies, MDPI, vol. 11(2), pages 1-19, February.
    4. Mohamed S. Abdalzaher & Hussein A. Elsayed & Mostafa M. Fouda & Mahmoud M. Salim, 2023. "Employing Machine Learning and IoT for Earthquake Early Warning System in Smart Cities," Energies, MDPI, vol. 16(1), pages 1-22, January.
    5. Imtiaz Parvez & Arif I. Sarwat & Longfei Wei & Aditya Sundararajan, 2016. "Securing Metering Infrastructure of Smart Grid: A Machine Learning and Localization Based Key Management Approach," Energies, MDPI, vol. 9(9), pages 1-18, August.
    6. Mohamed S. Abdalzaher & Mostafa M. Fouda & Mohamed I. Ibrahem, 2022. "Data Privacy Preservation and Security in Smart Metering Systems," Energies, MDPI, vol. 15(19), pages 1-19, October.
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    Cited by:

    1. Rui Zhang & Hao Zhang & Jianqiao Ye & Jiaqing Wang & Qing Liu & Shenghu Li, 2023. "Eigen-Sensitivity-Based Sliding Mode Control for LFO Damping in DFIG-Integrated Power Systems," Energies, MDPI, vol. 16(10), pages 1-18, May.
    2. Mohamed S. Abdalzaher & Moez Krichen & Derya Yiltas-Kaplan & Imed Ben Dhaou & Wilfried Yves Hamilton Adoni, 2023. "Early Detection of Earthquakes Using IoT and Cloud Infrastructure: A Survey," Sustainability, MDPI, vol. 15(15), pages 1-38, July.

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