Cited By
View all- Zhang YWang QMin SZuo RHuang FLiu HYao S(2025)Attention-based backdoor attacks against natural language processing modelsApplied Soft Computing10.1016/j.asoc.2025.112907173(112907)Online publication date: Apr-2025
Backdoor attacks aim to inject backdoors to victim machine learning models during training time, such that the backdoored model maintains the prediction power of the original model towards clean inputs and misbehaves towards backdoored inputs with the ...
With the rapid development of deep learning, its vulnerability has gradually emerged in recent years. This work focuses on backdoor attacks on speech recognition systems. We adopt sounds that are ordinary in nature or in our daily life as triggers ...
Speaker Verification (SV) is widely deployed in mobile systems to authenticate legitimate users by using their voice traits. In this work, we propose a backdoor attack MasterKey, to compromise the SV models. Different from previous attacks, we focus ...
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