Trustworthy Federated Learning via Blockchain

no code implementations • 13 Aug 2022 • Zhanpeng Yang, Yuanming Shi, Yong Zhou, Zixin Wang, Kai Yang

In this paper, we shall propose a decentralized blockchain based FL (B-FL) architecture by using a secure global aggregation algorithm to resist malicious devices, and deploying practical Byzantine fault tolerance consensus protocol with high effectiveness and low energy consumption among multiple edge servers to prevent model tampering from the malicious server.

Autonomous Driving Federated Learning +3

Communication-Efficient Edge AI Inference Over Wireless Networks

no code implementations • 28 Apr 2020 • Kai Yang, Yong Zhou, Zhanpeng Yang, Yuanming Shi

Given the fast growth of intelligent devices, it is expected that a large number of high-stake artificial intelligence (AI) applications, e. g., drones, autonomous cars, tactile robots, will be deployed at the edge of wireless networks in the near future.

Distributed Computing Edge-computing +1

Federated Machine Learning for Intelligent IoT via Reconfigurable Intelligent Surface

no code implementations • 13 Apr 2020 • Kai Yang, Yuanming Shi, Yong Zhou, Zhanpeng Yang, Liqun Fu, Wei Chen

Intelligent Internet-of-Things (IoT) will be transformative with the advancement of artificial intelligence and high-dimensional data analysis, shifting from "connected things" to "connected intelligence".

BIG-bench Machine Learning Self-Driving Cars