Fraud at the Interface: Synthetic Voice Exploits in Blockchain User Interaction Layers

The rapid convergence of synthetic voice technologies and blockchain-based financial systems creates unprecedented security vulnerabilities at user interaction interfaces. This position paper synthesizes current research on voice-enabled attack vectors targeting blockchain applications, analyzing the 1,300% surge in deepfake fraud attempts reported in 2024 and the resulting $4.6 billion in cryptocurrency-related losses. Through comprehensive literature review and threat modeling, we identify critical vulnerabilities in voice biometric systems that can be exploited in as few as six attempts using state-of-the-art synthesis algorithms. We propose a novel architectural framework integrating acoustic feature analysis, zero-knowledge proof protocols, and blockchain-based audit mechanisms. This research establishes theoretical foundations for securing next-generation voice-authenticated blockchain systems while addressing regulatory compliance challenges. Keywords: synthetic voice detection, blockchain security, voice biometrics, zero-knowledge proofs, threat modeling, cryptocurrency fraud