AI-Enhanced Mobile Digital Identity Frameworks for Secure Citizen Authentication
Keywords:
digital identity, mobile authentication, behavioral biometrics, artificial intelligence, blockchain, self-sovereign identity, zero trust architecture, multi-factor authentication, face recognition, keystroke dynamics, fraud detection, citizen identification.Abstract
Artificial Intelligence (AI) is increasingly being used to enhance citizen authentication and facilitate mass government and financial services. This paper brings together research from twenty-five sources up to 2022 to explore the convergence of behavioral biometrics, blockchain-based self-sovereign identity, federated identity management, and standardized assurance frameworks into architectures for mobile authentication enhanced by AI. The performance of continuous authentication methods developed on the bases of keystroke dynamics, gait patterns and facial recognition is compared based on the reported error rates, and the role of machine-learning based fraud detection mechanisms in transaction-level security is analyzed. Centralized and federated identity management systems are compared to blockchain identity management systems, such as redactable ledger schemes and verifiable-credential models, in terms of scalability, latency, and governance. The National Institute of Standards and Technology digital identity guidelines and zero trust architecture are normative benchmarks for the assurance-level classification. The case study covers one of the world's largest national biometric ID initiatives involving over one billion people, providing insight into the operational advantages and privacy challenges with centralized biometric ID infrastructures. Comparative analysis shows that hybrid architectures of continuous behavioural authentication and decentralized credential storage provide equal error rates lower than four percent and lower potential of single points of failure. It is demonstrated that the use of multi-factor authentication reduces the percentage of credential-based compromise that is present in single-factor authentication schemes. The synthesis indicates that AI-powered mobile identity solutions, combined with formal assurance models and privacy-preserving architectures, can be a technically feasible and socially responsible approach to authenticating citizens and point to unaddressed regulatory and equity issues that should be addressed.
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