activity
20182022
most citedBlackMarks: Blackbox Multibit Watermarking for Deep Neural Networks

41 citations · 95 across the 8 of their papers we have counts for

collaborators

11 papers

cs.LG20224 cited

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…

cs.AI2022

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…

cs.CR20221 cited

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…

cs.CR20226 cited

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…

cs.CR202133 cited

ESCORT: Ethereum Smart COntRacTs Vulnerability Detection using Deep Neural Network and Transfer Learning

Oliver Lutz, Huili Chen, Hossein Fereidooni +4

Ethereum smart contracts are automated decentralized applications on the blockchain that describe the terms of the agreement between buyers and sellers, reducing the need for trust…

cs.CR20219 cited

TAD: Trigger Approximation based Black-box Trojan Detection for AI

Xinqiao Zhang, Huili Chen, Farinaz Koushanfar

An emerging amount of intelligent applications have been developed with the surge of Machine Learning (ML). Deep Neural Networks (DNNs) have demonstrated unprecedented performance…