Zero Trust Architecture in AI Powered Financial Systems with Advanced Data Encryption Standards

Abstract

Financial systems powered by artificial intelligence (AI) are increasingly targeted by sophisticated cyber threats, insider attacks, and data breaches. Traditional perimeter-based security models are insufficient for modern decentralized and cloud-based financial infrastructures. This paper proposes for AI-powered financial systems, integrating advanced data encryption standards (AES, RSA, and elliptic curve cryptography) to ensure secure data access, storage, and computation. The architecture enforces continuous verification of users, devices, and AI workflows while employing strong cryptographic safeguards. Experimental evaluation demonstrates that the zero-trust framework combined with AI-driven monitoring significantly reduces the risk of unauthorized access and data leakage while maintaining high system performance. The proposed approach offers a resilient, scalable, and secure foundation for next-generation FinTech platforms.