32,462 research outputs found
Protecting Voice Controlled Systems Using Sound Source Identification Based on Acoustic Cues
Over the last few years, a rapidly increasing number of Internet-of-Things
(IoT) systems that adopt voice as the primary user input have emerged. These
systems have been shown to be vulnerable to various types of voice spoofing
attacks. Existing defense techniques can usually only protect from a specific
type of attack or require an additional authentication step that involves
another device. Such defense strategies are either not strong enough or lower
the usability of the system. Based on the fact that legitimate voice commands
should only come from humans rather than a playback device, we propose a novel
defense strategy that is able to detect the sound source of a voice command
based on its acoustic features. The proposed defense strategy does not require
any information other than the voice command itself and can protect a system
from multiple types of spoofing attacks. Our proof-of-concept experiments
verify the feasibility and effectiveness of this defense strategy.Comment: Proceedings of the 27th International Conference on Computer
Communications and Networks (ICCCN), Hangzhou, China, July-August 2018. arXiv
admin note: text overlap with arXiv:1803.0915
Universal Adversarial Perturbations for Speech Recognition Systems
In this work, we demonstrate the existence of universal adversarial audio
perturbations that cause mis-transcription of audio signals by automatic speech
recognition (ASR) systems. We propose an algorithm to find a single
quasi-imperceptible perturbation, which when added to any arbitrary speech
signal, will most likely fool the victim speech recognition model. Our
experiments demonstrate the application of our proposed technique by crafting
audio-agnostic universal perturbations for the state-of-the-art ASR system --
Mozilla DeepSpeech. Additionally, we show that such perturbations generalize to
a significant extent across models that are not available during training, by
performing a transferability test on a WaveNet based ASR system.Comment: Published as a conference paper at INTERSPEECH 201
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