打破安全关键语音认证

Andre Kassis, U. Hengartner
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摘要

语音认证(VA)最近已成为许多安全关键操作中不可或缺的一部分,例如银行交易和呼叫中心会话。自动说话人验证系统(asv)对欺骗攻击的脆弱性促使了对抗措施(CMs)的发展,其任务是区分真实语音和欺骗语音。asv和CMs共同构成了今天的VA系统,并被宣传为一种坚不可摧的访问控制机制。我们开发了欺骗对策的第一个实际攻击,并演示了恶意行为者如何有效地制作音频样本来对抗这些防御。以前针对VA的对抗性攻击主要是为白盒场景设计的,它假设了解系统内部,或者需要大量的查询和时间预算来发起特定目标的攻击。在攻击安全关键型系统时,这些假设就不成立了。另一方面,我们的攻击针对所有欺骗对策共享的常见故障点,使其成为实时的,模型不可知的,并且完全黑盒,而无需与目标交互来制作攻击样本。从我们的工作中得到的关键信息是,CMs错误地学习区分欺骗和真实的音频,基于容易识别和伪造的线索。我们的攻击效果非常微妙,足以保证这些对抗性样本仍然可以绕过ASV并保留其原始文本内容。这些属性结合在一起构成了一种强大的攻击,可以绕过安全关键的最严格形式的VA,只需6次尝试就能获得高达99%的成功率。最后,我们对CMs进行了第一次有针对性的电话网络攻击,绕过了几个已知的挑战,并使各种潜在威胁成为可能,因为呼叫中心越来越多地使用语音生物识别技术。我们的研究结果对现代VA系统的安全性提出了质疑,并敦促用户重新考虑他们对这些系统的信任,因为攻击者会绕过这些措施获得他们最宝贵的资源。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Breaking Security-Critical Voice Authentication
Voice authentication (VA) has recently become an integral part in numerous security-critical operations, such as bank transactions and call center conversations. The vulnerability of automatic speaker verification systems (ASVs) to spoofing attacks instigated the development of countermeasures (CMs), whose task is to differentiate between bonafide and spoofed speech. Together, ASVs and CMs form today’s VA systems and are being advertised as an impregnable access control mechanism. We develop the first practical attack on spoofing countermeasures, and demonstrate how a malicious actor may efficiently craft audio samples against these defenses. Previous adversarial attacks against VA have been mainly designed for the whitebox scenario, which assumes knowledge of the system’s internals, or requires large query and time budgets to launch target-specific attacks. When attacking a security-critical system, these assumptions do not hold. Our attack, on the other hand, targets common points of failure that all spoofing countermeasures share, making it real-time, model-agnostic, and completely blackbox without the need to interact with the target to craft the attack samples. The key message from our work is that CMs mistakenly learn to distinguish between spoofed and bonafide audio based on cues that are easily identifiable and forgeable. The effects of our attack are subtle enough to guarantee that these adversarial samples can still bypass the ASV as well and preserve their original textual contents. These properties combined make for a powerful attack that can bypass security-critical VA in its strictest form, yielding success rates of up to 99% with only 6 attempts. Finally, we perform the first targeted, over-telephony-network attack on CMs, bypassing several known challenges and enabling a variety of potential threats, given the increased use of voice biometrics in call centers. Our results call into question the security of modern VA systems and urge users to rethink their trust in them, in light of the real threat of attackers bypassing these measures to gain access to their most valuable resources.
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