BossPro: a biometrics-based obfuscation scheme for software protectionDate:2021-09-12
ANALYTICAL STUDY ON BIOMETRIC SECURITY APPLICATION IN INDUSTRIAL AND MOBILE BANKING SECTOR
Voice interface has been a dominant User Interface (UI) channel in the popular smart home environment. Although Voice Control System (VCS) brings users conveniences, it is extremely vulnerable to spoofing attacks (\eg, hidden/inaudible command attack) due to its broadcast nature. In this study, to thwart spoofing attacks, we propose WSVA, a device-free voice liveness detection system based on the prevalent wireless signals generated by IoT devices without requiring user to carry any additional sensor or device. The basic insight of WSVA to distinguish the authentic voice command from a spoofed one is checking the consistency between the voice signal and its corresponding mouth motions, which can be captured by wireless signals. WSVA firstly builds a theoretical model to describe the correlations among the wireless signal changes, the mouth motions, and the syllables in the voice command. Then, WSVA selects appropriate features from both voice and wireless signals, and calculates their consistency to determine whether the VCS is suffering from attack. We conduct a case study on Samsung SmartThings platform and evaluate WSVA with various voice commands in different scenarios. Experimental results demonstrate that WSVA achieves high detection accuracy with a good scalability and low latency.
A method of depositing items of value, the method comprising
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