In recent years, machine learning algorithms, and more specifically deep learning
algorithms, have been widely used in many fields, including cyber security. However …

Speech and speaker recognition systems are employed in a variety of applications, from
personal assistants to telephony surveillance and biometric authentication. The wide …

Deep Neural Networks have recently gained lots of success after enabling several
breakthroughs in notoriously challenging problems. Training these networks is …

The ASVspoof initiative was conceived to spearhead research in anti-spoofing for automatic
speaker verification (ASV). This paper describes the third in a series of bi-annual …

Speaker recognition (SR) is widely used in our daily life as a biometric authentication or
identification mechanism. The popularity of SR brings in serious security concerns, as …

Transferable adversarial attacks against Deep neural networks (DNNs) have received broad
attention in recent years. An adversarial example can be crafted by a surrogate model and …

Stealing attack against controlled information, along with the increasing number of
information leakage incidents, has become an emerging cyber security threat in recent …

Existing efforts in audio adversarial attacks only focus on the scenarios where an adversary
has prior knowledge of the entire speech input so as to generate an adversarial example by …

Adversarial attacks against commercial black-box speech platforms, including cloud speech
APIs and voice control devices, have received little attention until recent years. Constructing …

Recent studies have highlighted adversarial examples as a ubiquitous threat to different
neural network models and many downstream applications. Nonetheless, as unique data …