2 citations · 2 across the 1 of their papers we have counts for
5 papers
Understanding Impacts of Task Similarity on Backdoor Attack and Detection
Di Tang, Rui Zhu, XiaoFeng Wang +2
With extensive studies on backdoor attack and detection, still fundamental questions are left unanswered regarding the limits in the adversary's capability to attack and the defend…
Your Smart Home Can't Keep a Secret: Towards Automated Fingerprinting of IoT Traffic with Neural Networks
Shuaike Dong, Zhou Li, Di Tang +3
The IoT (Internet of Things) technology has been widely adopted in recent years and has profoundly changed the people's daily lives. However, in the meantime, such a fast-growing t…
Demon in the Variant: Statistical Analysis of DNNs for Robust Backdoor Contamination Detection
Di Tang, XiaoFeng Wang, Haixu Tang +1
A security threat to deep neural networks (DNN) is backdoor contamination, in which an adversary poisons the training data of a target model to inject a Trojan so that images carry…
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…
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…