A Survey of Threats Against Voice Authentication and Anti-Spoofing Systems
Kamel Kamel, Keshav Sood, Hridoy Sankar Dutta, Sunil Aryal

TL;DR
This survey reviews the evolving threat landscape against voice authentication and anti-spoofing systems, covering attack types, methodologies, datasets, and challenges to guide future secure system development.
Contribution
It provides a comprehensive, organized overview of modern threats, attack methodologies, and open challenges in voice authentication and anti-spoofing systems.
Findings
Identifies key attack vectors like deepfake and adversarial attacks.
Summarizes datasets and performance benchmarks.
Highlights open challenges for system robustness.
Abstract
Voice authentication has undergone significant changes from traditional systems that relied on handcrafted acoustic features to deep learning models that can extract robust speaker embeddings. This advancement has expanded its applications across finance, smart devices, law enforcement, and beyond. However, as adoption has grown, so have the threats. This survey presents a comprehensive review of the modern threat landscape targeting Voice Authentication Systems (VAS) and Anti-Spoofing Countermeasures (CMs), including data poisoning, adversarial, deepfake, and adversarial spoofing attacks. We chronologically trace the development of voice authentication and examine how vulnerabilities have evolved in tandem with technological advancements. For each category of attack, we summarize methodologies, highlight commonly used datasets, compare performance and limitations, and organize existing…
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