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An interesting approach to those eavesdropping devices in your life.
https://arxiv.org/pdf/2112.07076.pdf
ABSTRACT
Automatic speech recognition systems have created exciting possibilities for
applications, however they also enable opportunities for systematic eavesdropping.
We propose a method to camouflage a person’s voice over-the-air from these
systems without inconveniencing the conversation between people in the room.
standard adversarial attacks are not effective in real-time streaming situations because
the characteristics of the signal will have changed by the time the attack is
executed. We introduce predictive attacks, which achieve real-time performance by
forecasting the attack that will be the most effective in the future. Under real-time
constraints, our method jams the established speech recognition system Deep-
Speech 3.9x more than baselines as measured through word error rate, and 6.6x
more as measured through character error rate. We furthermore demonstrate our
approach is practically effective in realistic environments over physical distances.
https://arxiv.org/pdf/2112.07076.pdf
ABSTRACT
Automatic speech recognition systems have created exciting possibilities for
applications, however they also enable opportunities for systematic eavesdropping.
We propose a method to camouflage a person’s voice over-the-air from these
systems without inconveniencing the conversation between people in the room.
standard adversarial attacks are not effective in real-time streaming situations because
the characteristics of the signal will have changed by the time the attack is
executed. We introduce predictive attacks, which achieve real-time performance by
forecasting the attack that will be the most effective in the future. Under real-time
constraints, our method jams the established speech recognition system Deep-
Speech 3.9x more than baselines as measured through word error rate, and 6.6x
more as measured through character error rate. We furthermore demonstrate our
approach is practically effective in realistic environments over physical distances.