80 citations · 244 across the 14 of their papers we have counts for
5 papers · 1 filter
PerD: Perturbation Sensitivity-based Neural Trojan Detection Framework on NLP Applications
Diego Garcia-soto, Huili Chen, Farinaz Koushanfar
Deep Neural Networks (DNNs) have been shown to be susceptible to Trojan attacks. Neural Trojan is a type of targeted poisoning attack that embeds the backdoor into the victim and i…
Self-Aware Personalized Federated Learning
Huili Chen, Jie Ding, Eric Tramel +4
In the context of personalized federated learning (FL), the critical challenge is to balance local model improvement and global model tuning when the personal and global objectives…
AdaTest:Reinforcement Learning and Adaptive Sampling for On-chip Hardware Trojan Detection
Huili Chen, Xinqiao Zhang, Ke Huang +1
This paper proposes AdaTest, a novel adaptive test pattern generation framework for efficient and reliable Hardware Trojan (HT) detection. HT is a backdoor attack that tampers with…
An Adaptive Black-box Backdoor Detection Method for Deep Neural Networks
Xinqiao Zhang, Huili Chen, Ke Huang +1
With the surge of Machine Learning (ML), An emerging amount of intelligent applications have been developed. Deep Neural Networks (DNNs) have demonstrated unprecedented performance…
Backdoor Defense in Federated Learning Using Differential Testing and Outlier Detection
Yein Kim, Huili Chen, Farinaz Koushanfar
The goal of federated learning (FL) is to train one global model by aggregating model parameters updated independently on edge devices without accessing users' private data. Howeve…