Voice assistants (VA) have become prevalent on a wide range of personal devices such as
smartphones and smart speakers. As companies build voice assistants with extra …

Speaker recognition systems (SRSs) have recently been shown to be vulnerable to
adversarial attacks, raising significant security concerns. In this work, we systematically …

Cyber-security issues on adversarial attacks are actively studied in the field of computer
vision with the camera as the main sensor source to obtain the input image or video data …

Deep learning models have been widely used in commercial acoustic systems in recent
years. However, adversarial audio examples can cause abnormal behaviors for those …

DNN-based speaker recognition systems (SRSs) in smart cities suffer from adversarial
attacks, which have caused widespread concern. An attacker can fool the SRSs by adding …

Adversarial attacks have been expanded to speaker recognition (SR). However, existing
attacks are often assessed using different SR models, recognition tasks and datasets, and …

Abstract Audio Adversarial Examples (AAE) represent purposefully designed inputs meant
to trick Automatic Speech Recognition (ASR) systems into misclassification. The present …

Deep neural network (DNN), though widely applied in Speaker Recognition Systems (SRS),
is vulnerable to adversarial attacks which are hard to detect by humans. The black-box …

Automatic speech recognition (ASR) systems are known to be vulnerable to adversarial
attacks. This paper addresses detection and defence against targeted white-box attacks on …

With the rapid development of voice technology, speaker recognition is becoming
increasingly prevalent in our daily lives. However, with its increased usage, security issues …