AudioFool: Fast, Universal and synchronization-free Cross-Domain Attack
  on Speech Recognition
Mohamad Fakih Rouwaida Kanj Fadi Kurdahi Mohammed E. Fouda
Automatic Speech Recognition systems have been shown to be vulnerable to
adversarial attacks that manipulate the command executed on the device. Recent
research has focused on exploring methods to create such attacks, however, some
issues relating to Over-The-Air (OTA) attacks have not been properly addressed.
In our work, we examine the needed properties of robust attacks compatible with
the OTA model, and we design a method of generating attacks with arbitrary such
desired properties, namely the invariance to synchronization, and the
robustness to filtering: this allows a Denial-of-Service (DoS) attack against
ASR systems. We achieve these characteristics by constructing attacks in a
modified frequency domain through an inverse Fourier transform. We evaluate our
method on standard keyword classification tasks and analyze it in OTA, and we
analyze the properties of the cross-domain attacks to explain the efficiency of
the approach.