Abstract
Recently, there has been a surge in the popularity of voice-first devices, such as Amazon Echo, Google Home, etc. While these devices make our life more convenient, they are vulnerable to new attacks, such as voice replay. We develop an end-to-end system to detect replay attacks without requiring a user to wear any wearable device. Our system, called REVOLT, has several distinct features: (i) it intelligently exploits the inherent differences between the spectral characteristics of the original and replayed voice signals, (ii) it exploits both acoustic and WiFi channels in tandem, (iii) it utilizes unique breathing rate extracted from WiFi signal while speaking to test the liveness of human voice. After extensive evaluation, our voice component yields Equal Error Rate (EER) of 0.88% and 10.32% in our dataset and ASV2017 dataset, respectively; and WiFi based breathing detection achieves Breaths Per Minute (BPM) error of 1.8 up to 3m distance. We further combine WiFi and voice based detection and show the overall system offers low false positive and false negative when evaluated against a range of attacks.
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