Zero Trust AI-Powered Cybersecurity Framework for Cloud-Native Banking, Healthcare, and Government Systems
DOI:
https://doi.org/10.15680/IJCTECE.2025.0806029Keywords:
Zero Trust security, AI-powered cybersecurity, Cloud-native security, Banking cybersecurity, Healthcare data protection, Government cybersecurity, Machine learning security, Continuous authentication, Threat detection, Cloud infrastructure securityAbstract
The rapid digital transformation across banking, healthcare, and government sectors has significantly increased the reliance on cloud-native systems for storing, processing, and transmitting sensitive data. However, this transition has also expanded the attack surface, making these sectors prime targets for sophisticated cyber threats. Traditional perimeter-based security models are no longer sufficient to protect distributed and dynamic cloud environments. This paper proposes a Zero Trust AI-powered cybersecurity framework designed to secure cloud-native infrastructures used in critical sectors such as banking, healthcare, and government systems. The framework integrates Zero Trust principles, artificial intelligence–based threat detection, identity-centric security controls, and continuous monitoring mechanisms. By combining AI-driven analytics with strict access verification and automated threat response, the proposed framework strengthens data protection, improves real-time threat detection, and enhances resilience against advanced cyberattacks. The model ensures that every user, device, and application is continuously verified before accessing resources, thereby minimizing the risk of unauthorized access and data breaches.
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