# Backdoor Attacks against Voice Recognition Systems: A Survey

arXiv: https://arxiv.org/abs/2307.13643 · HTML: https://mlsanity.com/paper/2307.13643/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 23 Jul 2023.

## Built on by (most cited first, 6 of 6)

- [Beyond Boundaries: A Comprehensive Survey of Transferable Attacks on AI Systems](https://mlsanity.com/paper/2311.11796/) (2023)
- [Parasite: A Steganography-based Backdoor Attack Framework for Diffusion Models](https://mlsanity.com/paper/2504.05815/) (2025)
- [A Survey of Threats Against Voice Authentication and Anti-Spoofing Systems](https://mlsanity.com/paper/2508.16843/) (2025)
- [Gradient Norm-based Fine-Tuning for Backdoor Defense in Automatic Speech Recognition](https://mlsanity.com/paper/2502.01152/) (2025)
- [Investigating Vulnerabilities and Defenses Against Audio-Visual Attacks: A Comprehensive Survey Emphasizing Multimodal Models](https://mlsanity.com/paper/2506.11521/) (2025)
- [BackWeak: Backdooring Knowledge Distillation Simply with Weak Triggers and Fine-tuning](https://mlsanity.com/paper/2511.12046/) (2025)

## Abstract (arXiv)

Voice Recognition Systems (VRSs) employ deep learning for speech recognition and speaker recognition. They have been widely deployed in various real-world applications, from intelligent voice assistance to telephony surveillance and biometric authentication. However, prior research has revealed the vulnerability of VRSs to backdoor attacks, which pose a significant threat to the security and privacy of VRSs. Unfortunately, existing literature lacks a thorough review on this topic. This paper fills this research gap by conducting a comprehensive survey on backdoor attacks against VRSs. We first present an overview of VRSs and backdoor attacks, elucidating their basic knowledge. Then we propose a set of evaluation criteria to assess the performance of backdoor attack methods. Next, we present a comprehensive taxonomy of backdoor attacks against VRSs from different perspectives and analyze the characteristic of different categories. After that, we comprehensively review existing attack methods and analyze their pros and cons based on the proposed criteria. Furthermore, we review classic backdoor defense methods and generic audio defense techniques. Then we discuss the feasibility of deploying them on VRSs. Finally, we figure out several open issues and further suggest future research directions to motivate the research of VRSs security.