To Talk or to Work: Delay Efficient Federated Learning over Mobile Edge Devices

no code implementations • 1 Nov 2021 • Pavana Prakash, Jiahao Ding, Maoqiang Wu, Minglei Shu, Rong Yu, Miao Pan

Federated learning (FL), an emerging distributed machine learning paradigm, in conflux with edge computing is a promising area with novel applications over mobile edge devices.

Edge-computing Federated Learning

Evaluation of Inference Attack Models for Deep Learning on Medical Data

no code implementations • 31 Oct 2020 • Maoqiang Wu, Xinyue Zhang, Jiahao Ding, Hien Nguyen, Rong Yu, Miao Pan, Stephen T. Wong

This paper aims to attract interest from researchers in the medical deep learning community to this important problem.

Attribute Inference Attack

Blockchain for Secure and Efficient Data Sharing in Vehicular Edge Computing and Networks

no code implementations • IEEE INTERNET OF THINGS JOURNAL, VOL. 6, NO. 3 2018 • Jiawen Kang, Rong Y u, Xumin Huang, Maoqiang Wu, Sabita Maharjan, Member, Shengli Xie, and Y an Zhang, Senior Member, IEEE

Due to limited resources with vehicles, vehicular edge computing and networks (VECONs) i. e., the integration of mobile edge computing and vehicular networks, can provide powerful computing and massive storage resources.

Edge-computing