Personal voice assistants (VAs) are shown to be vulnerable against record-and-replay, and other acoustic attacks which allow an adversary to gain unauthorized control of connected devices within a smart home. Existing defenses either lack detection and management capabilities or are too coarse-grained to enable flexible policies on par with other computing interfaces. In this work, we present Sesame, a lightweight framework for edge devices which is the first to enable fine-grained access control of smart-home voice commands. Sesame combines three components: Automatic Speech Recognition, Natural Language Understanding (NLU) and a Policy module. We implemented Sesame on Android devices and demonstrate that our system can enforce security policies for both Alexa and Google Home in real-time (362ms end-to-end inference time), with a lightweight (<25MB) NLU model which exhibits minimal accuracy loss compared to its non-compact equivalent.
翻译:个人语音助理(VAs)被证明在记录和重播以及其他声学攻击中容易受到伤害,这些攻击使对手能够擅自控制智能家庭内的连接装置。现有的防御手段要么缺乏探测和管理能力,要么过于粗糙,无法与其他计算界面相提并论地采取灵活政策。在这项工作中,我们向Sesame展示了边缘装置的轻量框架,这一框架首先能够对智能家庭语音指令进行细微的进入控制。Sesame组合了三个组成部分:自动语音识别、自然语言理解(NLU)和政策模块。我们在Android装置上安装了Sesame,并表明我们的系统可以实时执行Alexa和Google Home的安全政策(362米端到端的推论时间),而轻量(<25MB)NLU模型显示精度损失与其非相近。