326 citations · 1.2k across the 19 of their papers we have counts for
5 papers · 1 filter
Understanding and Mitigating the Security Risks of Voice-Controlled Third-Party Skills on Amazon Alexa and Google Home
Nan Zhang, Xianghang Mi, Xuan Feng +3
Virtual personal assistants (VPA) (e.g., Amazon Alexa and Google Assistant) today mostly rely on the voice channel to communicate with their users, which however is known to be vul…
Invisible Mask: Practical Attacks on Face Recognition with Infrared
Zhe Zhou, Di Tang, Xiaofeng Wang +3
Accurate face recognition techniques make a series of critical applications possible: policemen could employ it to retrieve criminals' faces from surveillance video streams; cross…
Understanding Membership Inferences on Well-Generalized Learning Models
Yunhui Long, Vincent Bindschaedler, Lei Wang +5
Membership Inference Attack (MIA) determines the presence of a record in a machine learning model's training data by querying the model. Prior work has shown that the attack is fea…
Query-Free Attacks on Industry-Grade Face Recognition Systems under Resource Constraints
Di Tang, XiaoFeng Wang, Kehuan Zhang
To launch black-box attacks against a Deep Neural Network (DNN) based Face Recognition (FR) system, one needs to build \textit{substitute} models to simulate the target model, so t…
CommanderSong: A Systematic Approach for Practical Adversarial Voice Recognition
Xuejing Yuan, Yuxuan Chen, Yue Zhao +7
The popularity of ASR (automatic speech recognition) systems, like Google Voice, Cortana, brings in security concerns, as demonstrated by recent attacks. The impacts of such threat…