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Improving resilience and efficiency in the energy sector: A perspective on cybersecurity and renewable energy storage.

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  • Oluwadamilola Ogunleye,
  • Sulaimon Adeniji,
  • Valentine Onih,
  • Yufenyuy Simo,
  • Emmanuel Elom,
  • Emmanuel Kanu,
  • Abdul-Waliyyu Bello,
  • Callistus Obunadike,
  • Nnaji Chukwu,
  • Oluomachi Ejiofor,
  • Juliet Ogutu,
  • Chinenye Obunadike,
  • Tosin Clement,
  • Somto Kizor-Akaraiwe
Oluwadamilola Ogunleye
George Washington University, Washington DC, USA
Sulaimon Adeniji
University of Lagos, Lagos State
Valentine Onih
University of Hertfordshire, Hatfield,
Yufenyuy Simo
Austin Peay State University, Clarksville
Emmanuel Elom
Austin Peay State University, Clarksville
Emmanuel Kanu
Austin Peay State University, Clarksville
Abdul-Waliyyu Bello
Austin Peay State University, Clarksville
Callistus Obunadike
Austin Peay State University
Nnaji Chukwu
Austin Peay State University, Clarksville
Oluomachi Ejiofor
Austin Peay State University, Clarksville
Juliet Ogutu
Austin Peay State University, Clarksville
Chinenye Obunadike
Anambra State University Uli, Anambra State
Tosin Clement
George Washington University, Washington DC
Somto Kizor-Akaraiwe
George Washington University, Washington DC
Published in : International Journal of Scientific Research and Management (IJSRM) , Vol. 12 No. 05 (2024)

Published 2024-05-03

Keywords

  • Cybersecurity, Renewable energy, Energy Sector, Resilience, Energy Sector Efficiency.

Copyright (c) 2024 Oluwadamilola Ogunleye, Sulaimon Adeniji, Valentine Onih, Yufenyuy Simo, Emmanuel Elom, Emmanuel Kanu, Abdul-Waliyyu Bello, Callistus Obunadike, Nnaji Chukwu, Oluomachi Ejiofor, Juliet Ogutu, Chinenye Obunadike, Tosin Clement, Somto Kizor-Akaraiwe

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

Abstract

The study investigates how resilience and efficiency can be improved in the energy sector using cybersecurity. The main objective of the paper is to enable organizations in the energy sector to develop a robust framework to manage renewable  energy storage effectively with little to no cost consequence because of cyberattacks. A survey data saved in the repository of Kaggle was extracted and utilized for the purpose of the study, it contains cybersecurity indicators such as anomaly score, log source, attack types, attacks severity, and response action, which were the features adopted for developing a model, while the target variable was renewable energy generation. A machine learning approach was adopted, with the Rsquared indicating that 61 % variation in renewable energy store is explained by the features included in the model. The study recommends that there should be an increased investment in cybersecurity structure to safeguard energy systems against cyber threats. Also, stakeholders should implement comprehensive training programs to enhance cybersecurity awareness and skills of personnel working in the energy sector.

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