The emergence of Artificial Intelligence (AI)-driven audio attacks has revealed new security vulnerabilities in voice control systems. While researchers have introduced a multitude of attack strategies targeting voice control systems (VCS), the continual advancements of VCS have diminished the impact of many such attacks. Recognizing this dynamic landscape, our study endeavors to comprehensively assess the resilience of commercial voice control systems against a spectrum of malicious audio attacks. Through extensive experimentation, we evaluate six prominent attack techniques across a collection of voice control interfaces and devices. Contrary to prevailing narratives, our results suggest that commercial voice control systems exhibit enhanced resistance to existing threats. Particularly, our research highlights the ineffectiveness of white-box attacks in black-box scenarios. Furthermore, the adversaries encounter substantial obstacles in obtaining precise gradient estimations during query-based interactions with commercial systems, such as Apple Siri and Samsung Bixby. Meanwhile, we find that current defense strategies are not completely immune to advanced attacks. Our findings contribute valuable insights for enhancing defense mechanisms in VCS. Through this survey, we aim to raise awareness within the academic community about the security concerns of VCS and advocate for continued research in this crucial area.

翻译：人工智能驱动的音频攻击揭示了语音控制系统中的新安全漏洞。尽管研究人员已提出针对语音控制系统（VCS）的大量攻击策略，但VCS的持续进步削弱了许多此类攻击的影响。鉴于这一动态格局，本研究致力于全面评估商业语音控制系统在面对多种恶意音频攻击时的抵御能力。通过广泛实验，我们评估了六种主流攻击技术在各类语音控制接口与设备上的表现。与主流观点相反，我们的结果表明商业语音控制系统对现有威胁展现出更强的抵抗力。特别是，本研究凸显了白盒攻击在黑盒场景中的无效性。此外，攻击者在与商业系统（如Apple Siri和Samsung Bixby）进行基于查询的交互时，难以获得精确的梯度估计。同时，我们发现当前防御策略尚未完全免疫于高级攻击。我们的发现为增强VCS防御机制提供了宝贵见解。通过本调查，我们旨在提升学术界对VCS安全问题的关注，并倡导在这一关键领域持续推进研究。