Authors :
Jaya Chandra Myla
Volume/Issue :
Volume 10 - 2025, Issue 3 - March
Google Scholar :
https://tinyurl.com/y9u5zwm4
Scribd :
https://tinyurl.com/bdhphjk7
DOI :
https://doi.org/10.38124/ijisrt/25mar035
Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.
Abstract :
Government and public infrastructure are prime targets for cyber threats due to their critical role in national
security and public safety. The increasing sophistication of cyber-attacks necessitates the adoption of advanced
cybersecurity measures. This research explores the integration of Artificial Intelligence (AI)-driven threat detection and
response systems to enhance cybersecurity resilience in government and public infrastructure. It highlights AI's role in
real-time threat intelligence, anomaly detection, and automated mitigation strategies. The study further discusses
challenges, potential solutions, and future research directions in AI-driven cybersecurity frameworks.
Keywords :
Cyber-Attacks, Artificial Intelligence (AI)-Driven Threat Detection & Frameworks.
References :
- Anderson, J. (2024). Artificial Intelligence in Cybersecurity: A Comprehensive Review. Taylor & Francis.
- Brown, T., & Wilson, L. (2024). The Role of AI in Enhancing Threat Detection and Response in Cybersecurity Infrastructures. Cybersecurity Journal, 29(2), 145-167.
- Chen, X., & Zhou, Y. (2023). Enhancing Cyber Security through Artificial Intelligence and Machine Learning. Tech Science Press.
- Garcia, R., Martin, A., & Liu, S. (2023). Advancing Cybersecurity: AI-Driven Threat Detection and Response Systems in Critical Infrastructure. Springer.
- Kim, H., & Lee, J. (2024). AI and Cyber-Security: Enhancing Threat Detection and Response with Machine Learning. ResearchGate.
- Patel, M., Singh, R., & Chandra, P. (2023). AI-Driven Threat Detection and Response in Cybersecurity. International Journal of Cybersecurity, 11(3), 210-232.
- Smith, K., & Jones, P. (2024). Artificial Intelligence for Cybersecurity: Literature Review and Future Research Directions. IEEE Transactions on Cybersecurity, 19(1), 45-78.
- Wang, D., Zhang, X., & Thompson, C. (2023). AI-Driven Cybersecurity Solutions for Real-Time Threat Detection in Critical Infrastructure. Journal of Security Studies, 34(4), 189-215.
- Williams, B., Taylor, S., & Johnson, M. (2024). AI-Driven Threat Detection in Cybersecurity: A Paradigm Shift. Journal of Computer Security, 18(5), 89-110.
- Yaseen, A. (2023). AI-Driven Threat Detection and Response Systems for Secure National Infrastructure. International Journal of Information Security, 12(4), 67-92.
Government and public infrastructure are prime targets for cyber threats due to their critical role in national
security and public safety. The increasing sophistication of cyber-attacks necessitates the adoption of advanced
cybersecurity measures. This research explores the integration of Artificial Intelligence (AI)-driven threat detection and
response systems to enhance cybersecurity resilience in government and public infrastructure. It highlights AI's role in
real-time threat intelligence, anomaly detection, and automated mitigation strategies. The study further discusses
challenges, potential solutions, and future research directions in AI-driven cybersecurity frameworks.
Keywords :
Cyber-Attacks, Artificial Intelligence (AI)-Driven Threat Detection & Frameworks.