BoneAuth: A Bone-Conduction-Based Voice Liveness Authentication for Voice Assistants
Yue Li, Xueru Gao, Qipeng Song, Yao Wang, Pin Lyu, Haibin Zhang · IEEE Internet of Things Journal · 2024
As voice assistants (VAs) become increasingly popular, concerns about their privacy and security have garnered significant attention. VAs nowadays rely on voiceprint authentication to enhance their security. However, this method is susceptible to spoofing attacks, where attackers may use recording or synthesis techniques to mimic the user's voice, thereby bypassing the authentication mechanism. To address this, we introduce “BoneAuth,” a novel liveness detection system in this article. It offers continuous voice authentication for users, enhancing the security of VAs. BoneAuth is designed to be used in wearable devices with built-in microphones, such as Bluetooth earphones. Our basic idea is continuously matching the user's voice signals with the vibration signals produced by their vocal cords during speech. Specifically, our system uses the device's built-in microphone to concurrently capture vibrations from bone conduction (BC) and voices from air conduction (AC). We introduce a signal separation algorithm that, by measuring the unique threshold range of the user, can separate the AC and BC signals from the mixed microphone signals. By continuously comparing the consistency of the two signals, our system can determine whether the user's voice is a real live voice or artificially generated voice. Our system does not require user-specific passphrases for authentication, making it easy to deploy and use without the need for additional user actions or hardware. We demonstrate the feasibility of our method using commercial off-the-shelf Bluetooth earphones. Extensive experiments show an accuracy rate close to 98.15%, proving the effectiveness of our approach.