Real Time AI Based Cybersecurity for Cloud Enterprise Network Platforms in Government Financial and Healthcare Services

Andrea Marrella

doi:10.15662/IJRAI.2025.0804015

Authors

Andrea Marrella Senior Systems Engineer, Spain Author

DOI:

https://doi.org/10.15662/IJRAI.2025.0804015

Keywords:

Real-Time Artificial Intelligence, Cybersecurity, Cloud Computing, Enterprise Security Architecture, Government Digital Platforms, Financial Services Security, Healthcare Information Security, Threat Detection, Intrusion Detection Systems (IDS), Security Information and Event Management (SIEM), Zero Trust Architecture, Behavioral Analytics, Cloud Security Posture Management (CSPM), Data Privacy Compliance, Risk Management Frameworks

Abstract

Real-time Artificial Intelligence (AI)-based cybersecurity has become a strategic necessity for cloud enterprise network platforms supporting government, financial, and healthcare services. As digital transformation accelerates, critical infrastructures increasingly rely on cloud-native architectures, distributed networks, and interconnected applications. This expanded digital footprint exposes sensitive systems to advanced persistent threats, ransomware, insider attacks, and zero-day vulnerabilities. AI-driven cybersecurity leverages machine learning, behavioral analytics, and automated threat intelligence to detect, predict, and respond to cyber threats in real time.

Cloud service providers such as Amazon Web Services, Microsoft Azure, and Google Cloud integrate AI-powered security tools into enterprise cloud infrastructures, enabling continuous monitoring, anomaly detection, and automated incident response. In financial systems, AI enhances fraud detection and transaction monitoring. Healthcare institutions use AI to protect electronic health records and ensure regulatory compliance. Government platforms deploy AI-based security frameworks to safeguard digital identity systems, tax portals, and national data repositories.

This study explores architectural models, real-time detection mechanisms, security orchestration strategies, and governance frameworks required to implement AI-based cybersecurity within cloud enterprise networks. It evaluates technical, regulatory, and ethical dimensions while proposing a comprehensive research methodology to assess effectiveness, resilience, and sustainability.

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