AI-ENABLED DIGITAL IDENTITY VERIFICATION FRAMEWORK FOR GOVERNMENT SELF-SERVICE PLATFORMS USING SECURE API AND CLOUD INTEGRATION

Abstract

Digital government initiatives increasingly rely on self-service platforms to deliver citizen services efficiently, securely, and at scale. However, ensuring accurate and secure identity verification remains a major challenge due to rising cyber threats, identity fraud, and the complexity of integrating multiple government databases. This paper proposes an
Digital government initiatives increasingly rely on self-service platforms to deliver citizen services efficiently, securely, and at scale. However, ensuring accurate and secure identity verification remains a major challenge due to rising cyber threats, identity fraud, and the complexity of integrating multiple government databases. This paper proposes an AI-enabled digital identity verification framework designed for government self-service platforms that leverages secure API architectures, machine learning-based identity validation, and cloud-native integration models. The framework combines biometric verification, document authentication, and behavioral analytics to provide a multi-layered identity assurance mechanism.
The proposed architecture utilizes artificial intelligence techniques such as facial recognition, anomaly detection, and document classification to automate identity verification processes while maintaining compliance with government security and privacy regulations. Secure API gateways and microservice-based integration enable seamless connectivity between government databases, authentication providers, and cloud-based identity services. Cloud infrastructure further supports scalability, high availability, and real-time processing capabilities required for large-scale citizen service platforms.
Additionally, the study analyzes key design principles including data privacy protection, interoperability, fraud detection, and system resilience. Conceptual system models, workflow diagrams, and performance considerations are presented to demonstrate how the framework improves verification accuracy, reduces processing time, and enhances user trust in digital government services. The results indicate that AI-driven identity verification systems can significantly improve service delivery efficiency while strengthening security in digital governance ecosystems. The proposed framework provides a scalable blueprint for governments seeking to modernize citizen authentication mechanisms in secure cloud-based environments.