77 citations · 103 across the 11 of their papers we have counts for
11 papers
Toward Evaluating Robustness of Reinforcement Learning with Adversarial Policy
Xiang Zheng, Xingjun Ma, Shengjie Wang +3
Reinforcement learning agents are susceptible to evasion attacks during deployment. In single-agent environments, these attacks can occur through imperceptible perturbations inject…
Amplifying Membership Exposure via Data Poisoning
Yufei Chen, Chao Shen, Yun Shen +2
As in-the-wild data are increasingly involved in the training stage, machine learning applications become more susceptible to data poisoning attacks. Such attacks typically lead to…
Black-box Adversarial Attacks on Commercial Speech Platforms with Minimal Information
Baolin Zheng, Peipei Jiang, Qian Wang +6
Adversarial attacks against commercial black-box speech platforms, including cloud speech APIs and voice control devices, have received little attention until recent years. The cur…
Securing Face Liveness Detection Using Unforgeable Lip Motion Patterns
Man Zhou, Qian Wang, Qi Li +5
Face authentication usually utilizes deep learning models to verify users with high recognition accuracy. However, face authentication systems are vulnerable to various attacks tha…
CARTL: Cooperative Adversarially-Robust Transfer Learning
Dian Chen, Hongxin Hu, Qian Wang +4
Transfer learning eases the burden of training a well-performed model from scratch, especially when training data is scarce and computation power is limited. In deep learning, a ty…
Teacher Model Fingerprinting Attacks Against Transfer Learning
Yufei Chen, Chao Shen, Cong Wang +1
Transfer learning has become a common solution to address training data scarcity in practice. It trains a specified student model by reusing or fine-tuning early layers of a well-t…