most citedLoMar: A Local Defense Against Poisoning Attack on Federated Learning

5 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.NI2023★ 1 cited

Data-Driven Next-Generation Wireless Networking: Embracing AI for Performance and Security

Jiahao Xue, Zhe Qu, Shangqing Zhao +2

New network architectures, such as the Internet of Things (IoT), 5G, and next-generation (NextG) cellular systems, put forward emerging challenges to the design of future wireless…

cs.DC2022

On the Convergence of Multi-Server Federated Learning with Overlapping Area

Zhe Qu, Xingyu Li, Jie Xu +3

Multi-server Federated learning (FL) has been considered as a promising solution to address the limited communication resource problem of single-server FL. We consider a typical mu…

cs.SD2022★ 2 cited

Perception-Aware Attack: Creating Adversarial Music via Reverse-Engineering Human Perception

Rui Duan, Zhe Qu, Shangqing Zhao +3

Recently, adversarial machine learning attacks have posed serious security threats against practical audio signal classification systems, including speech recognition, speaker reco…

cs.LG2022★ 5 cited

LoMar: A Local Defense Against Poisoning Attack on Federated Learning

Xingyu Li, Zhe Qu, Shangqing Zhao +3

Federated learning (FL) provides a high efficient decentralized machine learning framework, where the training data remains distributed at remote clients in a network. Though FL en…

cs.CR2022

IoTGAN: GAN Powered Camouflage Against Machine Learning Based IoT Device Identification

Tao Hou, Tao Wang, Zhuo Lu +2

With the proliferation of IoT devices, researchers have developed a variety of IoT device identification methods with the assistance of machine learning. Nevertheless, the security…