AI-Driven Risk Assessment in National Security Projects: Investigating machine learning models to predict and mitigate risks in defense and critical infrastructure projects

Authors

  • Md Habibul Arif MS in Information Technology, Washington University of Science and Technology, USA
  • Habibor Rahman Rabby MS in Computer Science, Campbellsville University, Kentucky, USA
  • Nusrat Yasmin Nadia MS in Information Technology, Washington University of Science and Technology, USA
  • Md Iftekhar Monzur Tanvir MS in Information Technology, Washington University of Science & Technology, Virginia, USA
  • Abdullah Al Masum MS in Information Technology 2025, Westcliff University, USA

DOI:

https://doi.org/10.32996/jcsts.2025.7.2.6

Keywords:

Artificial Intelligence (AI), Machine Learning (ML), Cybersecurity, National Security, Risk Assessment, Threat Intelligence, Critical Infrastructure Protection, Predictive Analytics, AI Ethics, Cyber Risk Management, Deep Learning, AI-Driven Defense Strategies

Abstract

Artificial Intelligence (AI) is revolutionizing national security and risk assessment, providing enhanced predictive capabilities, automated threat detection, and strategic decision-making tools. This paper explores the integration of AI and machine learning (ML) in national defense strategies, cybersecurity frameworks, and critical infrastructure protection. AI-driven risk assessment models utilize big data analytics, deep learning, and predictive algorithms to proactively identify, classify, and mitigate security threats before they materialize. The study examines AI applications in cyber risk management, military defense systems, fraud prevention, and digital forensics, highlighting their effectiveness in safeguarding government agencies, financial institutions, and energy grids. Additionally, the paper discusses ethical considerations, algorithmic biases, and regulatory challenges associated with AI-driven risk assessment. The findings emphasize the increasing reliance on AI in cybersecurity and national security operations, demonstrating how AI-based risk assessment tools contribute to threat intelligence, operational resilience, and automated decision-making in critical security environments. The research concludes with future directions for AI adoption, emerging innovations, and policy recommendations to ensure ethical and effective deployment of AI in national security frameworks.

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Published

2025-04-05

Issue

Vol. 7 No. 2

Section

Research Article

License

Creative Commons License

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

How to Cite

Md Habibul Arif, Habibor Rahman Rabby, Nusrat Yasmin Nadia, Md Iftekhar Monzur Tanvir, & Abdullah Al Masum. (2025). AI-Driven Risk Assessment in National Security Projects: Investigating machine learning models to predict and mitigate risks in defense and critical infrastructure projects. Journal of Computer Science and Technology Studies, 7(2), 71-85. https://doi.org/10.32996/jcsts.2025.7.2.6