activity
20152022
most citedBackdoor Attacks and Countermeasures on Deep Learning: A Comprehensive Review

133 citations · 222 across the 17 of their papers we have counts for

collaborators

23 papers

cs.CR20225 cited

Towards A Critical Evaluation of Robustness for Deep Learning Backdoor Countermeasures

Huming Qiu, Hua Ma, Zhi Zhang +4

Since Deep Learning (DL) backdoor attacks have been revealed as one of the most insidious adversarial attacks, a number of countermeasures have been developed with certain assumpti…

cs.CR20222 cited

Systematically Evaluation of Challenge Obfuscated APUFs

Yansong Gao, Jianrong Yao, Lihui Pang +4

As a well-known physical unclonable function that can provide huge number of challenge response pairs (CRP) with a compact design and fully compatibility with current electronic fa…

astro-ph.HE2022

Physical Publicly Verifiable Randomness from Pulsars

J. R. Dawson, George Hobbs, Yansong Gao +8

We demonstrate how radio pulsars can be used as random number generators. Specifically, we focus on publicly verifiable randomness (PVR), in which the same sequence of trusted and…

cs.CV202216 cited

Dangerous Cloaking: Natural Trigger based Backdoor Attacks on Object Detectors in the Physical World

Hua Ma, Yinshan Li, Yansong Gao +7

Deep learning models have been shown to be vulnerable to recent backdoor attacks. A backdoored model behaves normally for inputs containing no attacker-secretly-chosen trigger and…

cs.CR2021

SEDML: Securely and Efficiently Harnessing Distributed Knowledge in Machine Learning

Yansong Gao, Qun Li, Yifeng Zheng +3

Training high-performing deep learning models require a rich amount of data which is usually distributed among multiple data sources in practice. Simply centralizing these multi-so…

cs.LG20211 cited

Evaluation and Optimization of Distributed Machine Learning Techniques for Internet of Things

Yansong Gao, Minki Kim, Chandra Thapa +5

Federated learning (FL) and split learning (SL) are state-of-the-art distributed machine learning techniques to enable machine learning training without accessing raw data on clien…