most citedMan-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models

3 citations · 3 across the 1 of their papers we have counts for

collaborators

3 papers

cs.CR2019★ 3 cited

Man-in-the-Middle Attacks against Machine Learning Classifiers via Malicious Generative Models

Derui, Wang, Chaoran Li +3

Deep Neural Networks (DNNs) are vulnerable to deliberately crafted adversarial examples. In the past few years, many efforts have been spent on exploring query-optimisation attacks…

cs.CV2019

Daedalus: Breaking Non-Maximum Suppression in Object Detection via Adversarial Examples

Derui Wang, Chaoran Li, Sheng Wen +4

This paper demonstrates that Non-Maximum Suppression (NMS), which is commonly used in Object Detection (OD) tasks to filter redundant detection results, is no longer secure. Consid…

cs.LG2018

Defending against Adversarial Attack towards Deep Neural Networks via Collaborative Multi-task Training

Derek Wang, Chaoran Li, Sheng Wen +2

Deep neural networks (DNNs) are known to be vulnerable to adversarial examples which contain human-imperceptible perturbations. A series of defending methods, either proactive defe…