WiVo:通过无线信号增强物联网环境下语音控制系统的安全性

Yan Meng, Zichang Wang, Wei Zhang, Peilin Wu, Haojin Zhu, Xiaohui Liang, Yao Liu
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引用次数: 59

摘要

随着智能设备和家庭自动化的普及,语音命令已成为物联网环境中流行的用户界面(UI)通道。语音控制系统(VCS)虽然具有极大的便捷性,但由于其广播性,极易受到欺骗攻击(如重播攻击、隐藏/听不见命令攻击)。在本研究中,我们提出了WiVo,一种基于物联网设备产生的流行无线信号的无设备语音活跃度检测系统,无需用户携带任何额外的设备或传感器。WiVo的基本动机是通过相应的嘴部运动来区分真实的语音命令和欺骗的语音命令,这些嘴部运动可以被无线信号捕获和识别。为了实现这一目标,WiVo建立了一个理论模型来表征无线信号动态与用户语音音节之间的相关性。WiVo从语音和无线信号中提取独特的特征,然后计算这些不同类型信号之间的一致性,以确定语音命令是由VCS的真实用户还是攻击者生成的。为了评估WiVo的有效性,我们基于Samsung SmartThings框架构建了一个测试平台,并将WiVo作为一个新的应用纳入其中,预计将大大提高现有VCS的安全性。我们用6名参与者和不同的语音命令对WiVo进行了评估。实验评估结果表明,WiVo总体检测率达到99%,误接受率为1%,并且具有较低的延迟。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
WiVo: Enhancing the Security of Voice Control System via Wireless Signal in IoT Environment
With the prevalent of smart devices and home automations, voice command has become a popular User Interface (UI) channel in the IoT environment. Although Voice Control System (VCS) has the advantages of great convenience, it is extremely vulnerable to the spoofing attack (e.g., replay attack, hidden/inaudible command attack) due to its broadcast nature. In this study, we present WiVo, a device-free voice liveness detection system based on the prevalent wireless signals generated by IoT devices without any additional devices or sensors carried by the users. The basic motivation of WiVo is to distinguish the authentic voice command from a spoofed one via its corresponding mouth motions, which can be captured and recognized by wireless signals. To achieve this goal, WiVo builds a theoretical model to characterize the correlation between wireless signal dynamics and the user's voice syllables. WiVo extracts the unique features from both voice and wireless signals, and then calculates the consistency between these different types of signals in order to determine whether the voice command is generated by the authentic user of VCS or an adversary. To evaluate the effectiveness of WiVo, we build a testbed based on Samsung SmartThings framework and include WiVo as a new application, which is expected to significantly enhance the security of the existing VCS. We have evaluated WiVo with 6 participants and different voice commands. Experimental evaluation results demonstrate that WiVo achieves the overall 99% detection rate with 1% false accept rate and has a low latency.
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