Enhancing federal cloud security with AI: Zero trust, threat intelligence and CISA Compliance

Ofili, Bukunmi Temiloluwa and Erhabor, Emmanuella Osaruwenese and Obasuyi, Oghogho Timothy (2025) Enhancing federal cloud security with AI: Zero trust, threat intelligence and CISA Compliance. World Journal of Advanced Research and Reviews, 25 (2). pp. 2377-2400. ISSN 2581-9615

The increasing adoption of cloud computing by federal agencies has introduced significant security challenges, necessitating robust strategies to protect sensitive government data. Traditional perimeter-based security models are no longer sufficient against evolving cyber threats, leading to the need for Zero Trust Architecture (ZTA), AI-driven threat intelligence, and compliance with Cybersecurity and Infrastructure Security Agency (CISA) frameworks. This paper explores how artificial intelligence (AI) enhances federal cloud security by enabling adaptive access controls, automated anomaly detection, and real-time threat response. Zero Trust Architecture (ZTA) eliminates implicit trust in network environments by enforcing continuous verification of users, devices, and workloads. AI augments ZTA by leveraging machine learning (ML) algorithms to detect insider threats, automate authentication, and enforce least-privilege access. Additionally, AI-powered threat intelligence systems improve incident detection and response by analyzing vast data streams to identify attack patterns, phishing attempts, and ransomware indicators in real time. Ensuring compliance with CISA’s cloud security directives is essential for safeguarding federal systems against cyber threats. AI-driven compliance automation tools facilitate real-time monitoring of cloud configurations, detect policy violations, and support continuous diagnostics and mitigation (CDM) strategies. By integrating AI with ZTA and threat intelligence, federal agencies can proactively address cloud security risks, reduce attack surfaces, and strengthen their cyber resilience. This study highlights the transformative role of AI in enhancing federal cloud security, emphasizing the need for intelligent automation, predictive analytics, and regulatory alignment to secure critical infrastructures. Future research should focus on refining AI models for adaptive security orchestration, deception techniques, and proactive threat hunting in federal cloud environments