Tokenizing Trust: Leveraging Blockchain and AI to Develop Next-Generation Two-Factor Authentication

Abstract

Strong, scalable, and transparent authentication systems are desperately needed, as seen by the rapid development of digital ecosystems. In order to improve security and user trust, The paper introduces an adaptive risk-based framework for next-generation two-factor authentication (2FA), combining blockchain-based blind tokenization with AI-driven risk assess-ment. Further, this article integrates AI algorithms to evaluate contextual and behavioral patterns in real-time, while securing the second authentication factor through decentralized token generation and storage on a blockchain network. While tokenization substitutes dynamic cryptographically protected tokens for traditional static credentials, the blockchain component offers an immutable ledger that guarantees data integrity and resistance to tampering. The AI module concurrently keeps an eye on usage trends and irregularities to reduce threats like phishing and man-in-the-middle assaults. Initial simulations show that the combined method improves user authentication effectiveness without sacrificing usability and lessens typical weaknesses seen in conventional 2FA systems. By providing a decentralized, flexible, and affordable solution that balances the requirements of privacy, real-time intelligence, and secure distributed ledger technology, this study adds to the developing field of security architectures.