AI-Driven Approaches to Enhancing Digital Wallet Security in the Face of Evolving Threats

Abstract

As digital wallets become more ubiquitous, ensuring their security against an ever-growing landscape of cyber threats is paramount. AI-driven approaches offer innovative solutions to safeguard digital wallets by leveraging machine learning (ML) algorithms, anomaly detection techniques, and behavioral biometrics to counteract fraud, unauthorized access, and data breaches. This paper examines the evolving threats to digital wallet security and explores how AI technologies can be integrated into digital wallet systems to provide robust, adaptive, and intelligent protection mechanisms. Through experiments and results derived from various AI-based security models, the research outlines the effectiveness of these solutions in mitigating common and sophisticated attacks. The findings underscore the importance of adopting AI-driven security systems in future-proofing digital wallets