IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v16y2023i10p3997-d1142989.html
   My bibliography  Save this article

Security of Neural Network-Based Key Agreement Protocol for Smart Grids

Author

Listed:
  • Miłosz Stypiński

    (Institute of Telecommunications, AGH University of Krakow, Mickiewicza 30, 30-059 Krakow, Poland)

  • Marcin Niemiec

    (Institute of Telecommunications, AGH University of Krakow, Mickiewicza 30, 30-059 Krakow, Poland)

Abstract

Recent developments in quantum computing pose a significant threat to the asymmetric cryptography currently in use. Neural cryptography offers a potential alternative that is resistant to attacks of known quantum computer algorithms. The considered solution is lightweight and computationally efficient. If a quantum computer algorithm were successfully implemented, it could expose IoT sensors and smart grid components to a wide range of attack vectors. Given the lightweight nature of neural cryptography and the potential risks, neural cryptography could have potential applications in both IoT sensors and smart grid systems. This paper evaluates one of the suggested enhancements: the use of integer-valued input vectors that accelerate the synchronization of the Tree Parity Machine. This enhancement introduces a new parameter M that indicates the minimum and maximum values of input vector elements. This study evaluates the nonbinary version of the mutual learning algorithm in a simulated insecure environment. The results indicate that, while the Nonbinary Tree Parity Machine may involve some trade-offs between security and synchronization time, the speed improvement is more substantial than the decrease in security. The impact of this enhancement is particularly significant for smaller adjustments to parameter M .

Suggested Citation

  • Miłosz Stypiński & Marcin Niemiec, 2023. "Security of Neural Network-Based Key Agreement Protocol for Smart Grids," Energies, MDPI, vol. 16(10), pages 1-11, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:3997-:d:1142989
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/16/10/3997/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/16/10/3997/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Athira M. Mohan & Nader Meskin & Hasan Mehrjerdi, 2020. "A Comprehensive Review of the Cyber-Attacks and Cyber-Security on Load Frequency Control of Power Systems," Energies, MDPI, vol. 13(15), pages 1-33, July.
    Full references (including those not matched with items on IDEAS)

    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. Agbodoh-Falschau, Kouassi Raymond & Ravaonorohanta, Bako Harinivo, 2023. "Investigating the influence of governance determinants on reporting cybersecurity incidents to police: Evidence from Canadian organizations’ perspectives," Technology in Society, Elsevier, vol. 74(C).
    2. Xinghua Liu & Siwei Qiao & Zhiwei Liu, 2023. "A Survey on Load Frequency Control of Multi-Area Power Systems: Recent Challenges and Strategies," Energies, MDPI, vol. 16(5), pages 1-22, February.
    3. Félix Dubuisson & Miloud Rezkallah & Hussein Ibrahim & Ambrish Chandra, 2021. "Real-Time Implementation of the Predictive-Based Control with Bacterial Foraging Optimization Technique for Power Management in Standalone Microgrid Application," Energies, MDPI, vol. 14(6), pages 1-15, March.
    4. Marilena Stănculescu & Sorin Deleanu & Paul Cristian Andrei & Horia Andrei, 2021. "A Case Study of an Industrial Power Plant under Cyberattack: Simulation and Analysis," Energies, MDPI, vol. 14(9), pages 1-20, April.
    5. Mishra, Dillip Kumar & Ray, Prakash Kumar & Li, Li & Zhang, Jiangfeng & Hossain, M.J. & Mohanty, Asit, 2022. "Resilient control based frequency regulation scheme of isolated microgrids considering cyber attack and parameter uncertainties," Applied Energy, Elsevier, vol. 306(PA).
    6. Vijayshankar, Sanjana & Chang, Chin-Yao & Utkarsh, Kumar & Wald, Dylan & Ding, Fei & Balamurugan, Sivasathya Pradha & King, Jennifer & Macwan, Richard, 2023. "Assessing the impact of cybersecurity attacks on energy systems," Applied Energy, Elsevier, vol. 345(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:16:y:2023:i:10:p:3997-:d:1142989. 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.