1.9k citations · 2.4k across the 10 of their papers we have counts for
4 papers · 1 filter
Seeing isn't Believing: Practical Adversarial Attack Against Object Detectors
Yue Zhao, Hong Zhu, Ruigang Liang +3
In this paper, we presented systematic solutions to build robust and practical AEs against real world object detectors. Particularly, for Hiding Attack (HA), we proposed the featur…
DLFuzz: Differential Fuzzing Testing of Deep Learning Systems
Jianmin Guo, Yu Jiang, Yue Zhao +2
Deep learning (DL) systems are increasingly applied to safety-critical domains such as autonomous driving cars. It is of significant importance to ensure the reliability and robust…
Federated Learning with Non-IID Data
Yue Zhao, Meng Li, Liangzhen Lai +3
Federated learning enables resource-constrained edge compute devices, such as mobile phones and IoT devices, to learn a shared model for prediction, while keeping the training data…
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…