Enhancing Cybersecurity Resilience in Government and Public Infrastructure: AI-Driven Threat Detection and Response Systems


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 :

  1. Anderson, J. (2024). Artificial Intelligence in Cybersecurity: A Comprehensive Review. Taylor & Francis.
  2. Brown, T., & Wilson, L. (2024). The Role of AI in Enhancing Threat Detection and Response in Cybersecurity Infrastructures. Cybersecurity Journal, 29(2), 145-167.
  3. Chen, X., & Zhou, Y. (2023). Enhancing Cyber Security through Artificial Intelligence and Machine Learning. Tech Science Press.
  4. Garcia, R., Martin, A., & Liu, S. (2023). Advancing Cybersecurity: AI-Driven Threat Detection and Response Systems in Critical Infrastructure. Springer.
  5. Kim, H., & Lee, J. (2024). AI and Cyber-Security: Enhancing Threat Detection and Response with Machine Learning. ResearchGate.
  6. Patel, M., Singh, R., & Chandra, P. (2023). AI-Driven Threat Detection and Response in Cybersecurity. International Journal of Cybersecurity, 11(3), 210-232.
  7. Smith, K., & Jones, P. (2024). Artificial Intelligence for Cybersecurity: Literature Review and Future Research Directions. IEEE Transactions on Cybersecurity, 19(1), 45-78.
  8. 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.
  9. Williams, B., Taylor, S., & Johnson, M. (2024). AI-Driven Threat Detection in Cybersecurity: A Paradigm Shift. Journal of Computer Security, 18(5), 89-110.
  10. 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.

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