activity
20192024
most citedBlack-box Adversarial Attacks on Commercial Speech Platforms with Minimal Information

77 citations · 142 across the 15 of their papers we have counts for

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Showing 2021Show all

5 papers · 1 filter

cs.CR2021★ 77 cited

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…

cs.CR2021★ 4 cited

Property Inference Attacks Against GANs

Junhao Zhou, Yufei Chen, Chao Shen +1

While machine learning (ML) has made tremendous progress during the past decade, recent research has shown that ML models are vulnerable to various security and privacy attacks. So…

cs.CR2021★ 7 cited

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…

cs.LG2021

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…

cs.CR2021★ 3 cited

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…