Open Access

An Intelligent Risk-Aware Security Framework for Detection and Prevention of Cyber Attacks on Critical Power Grid Infrastructure in Nigeria’s Electricity Sector

https://doi.org/10.55640/ijctisn-v03i08-02

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Dr. Chinedu Okafor ¹ , Dr. Aisha Bello ¹ ,

⁴ Department of Cyber Security University of Lagos, Lagos, Nigeria

⁴ School of Computing Ahmadu Bello University, Zaria, Nigeria

Abstract

The increasing digitization of electric power systems has significantly expanded the attack surface of critical infrastructure, particularly within developing economies such as Nigeria, where grid modernization is still evolving. This study proposes an intelligent risk-aware security framework designed to detect, assess, and mitigate cyber attacks targeting critical power grid infrastructure in Nigeria’s electricity sector. The framework integrates threat intelligence, risk scoring, anomaly detection, and adaptive response mechanisms to enhance resilience against advanced persistent threats, including false data injection, GPS spoofing, SCADA manipulation, and IoT-based intrusions. Building on established cybersecurity models such as NIST cybersecurity framework principles and ENISA threat intelligence reports, the proposed system introduces a layered defense architecture tailored to smart grid environments. Machine learning-driven detection mechanisms, particularly deep learning models for anomaly recognition in phasor measurement units, are incorporated to improve detection accuracy (ALmutairy, Scekic & Wshah, 2022). The study synthesizes existing literature on cyber-physical power systems and identifies critical gaps in real-time risk prioritization and localized threat adaptation. The findings demonstrate that integrating risk-aware analytics with adaptive control significantly improves system resilience and reduces response latency. The research contributes a structured, scalable framework suitable for deployment in Nigeria’s power infrastructure and similar emerging grid environments.

Keywords

Cybersecurity, Smart Grid, Risk-Aware Framework, Power System Security

References

ALmutairy, F., Scekic, L., & Wshah, S.. (2022). Detection and Mitigation of GPS Spoofing Attacks against Phasor Measurement Units using Deep Learning. IEEE Transaction on Smart Grids.

Komninos, C., Survey, A., Grid, S., Komninos, N., Philippou, E., Pitsillides, A., & Member, S. (2014). City Research Online City , University of London Institutional Repository Survey in Smart Grid and Smart Home Security : Issues , Challenges and Countermeasures.

Larouche, JB., Roy, S., Mailhot, F., Tardif, PM & Frappier, M. (2023). SCADA Radio Blackbox Reverse Engineering. In: Jourdan, GV., Mounier, L., Adams, C., Sèdes, F., Garcia-Alfaro, J. (eds) Foundations and Practice of Security. FPS 2022. Lecture Notes in Computer Science, vol 13877. Springer, Cham.

Lee, S., Lee, S., & Kim, J. (2016). A Study on Security Vulnerability Management in Electric Power Industry IoT, 17(6), 499–507.

Livingston, Sanborn and Slaughter, Z. (2019). Managing cyber risk in the electric power sector | Deloitte Insights.

Marinos, L. (2013). European Union Agency for Network and Information Security Smart Grid Threat Landscape and Good Practice Guide Smart Grid Threat Landscape and Good Practice Guide About ENISA Smart Grid Threat Landscape and Good Practice Guide, (December).

Marinos, L., & Lourenço, M. (2018). ENISA Threat Landscape Report 2018 15 Top Cyberthreats and Trends. European Union Agency For Network and Information Security.

Mendel, J. (2017). Smart Grid Cyber Security Challenges: Overview and Classification. E-Mentor, 2017(1(68)), 55–66.

Mission Support Center Idaho National Laboratory. (2017). Cyber Threat and Vulnerability Analysis of the U.S. Electric Sector. Inl (Idaho National Laboratory), (August), 2–41.

National Cybersecurity Policy, & Nigeria, C. National Cybersecurity Policy of Nigeria (2014).

NIST; Roadmap for Smart Grid Interoperability. (2012). NIST Special Publication 1108R2 NIST Framework and Roadmap for Smart Grid Interoperability Standards.

NIST: Improving Critical Infrastructure Cybersecurity. (2014). Framework for improving critical infrastructure cybersecurity: Version 1.0.

Suprabhath K, S.; Machina, V.S.P & Madichetty, S. (2023) Cyber-attacks in Cyber-Physical Microgrid Systems: A Comprehensive Review. Preprints.org 2023, 2023040691.

Yang T, Liu Y & Li W. (2022). Attack and defence methods in cyber-physical power system. IET Energy Systems Integration, 4 (2):159–70.

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An Intelligent Risk-Aware Security Framework for Detection and Prevention of Cyber Attacks on Critical Power Grid Infrastructure in Nigeria’s Electricity Sector

Abstract

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References

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