14 citations · 26 across the 7 of their papers we have counts for
7 papers
PIGDreamer: Privileged Information Guided World Models for Safe Partially Observable Reinforcement Learning
Dongchi Huang, Jiaqi Wang, Yang Li +3
Partial observability presents a significant challenge for Safe Reinforcement Learning (Safe RL), as it impedes the identification of potential risks and rewards. Leveraging specif…
FLSSM: A Federated Learning Storage Security Model with Homomorphic Encryption
Yang Li, Chunhe Xia, Chang Li +2
Federated learning based on homomorphic encryption has received widespread attention due to its high security and enhanced protection of user data privacy. However, the characteris…
BFLN: A Blockchain-based Federated Learning Model for Non-IID Data
Yang Li, Chunhe Xia, Dongchi Huang +2
As the application of federated learning becomes increasingly widespread, the issue of imbalanced training data distribution has emerged as a significant challenge. Federated learn…
PPBFL: A Privacy Protected Blockchain-based Federated Learning Model
Yang Li, Chunhe Xia, Wanshuang Lin +1
With the rapid development of machine learning and a growing concern for data privacy, federated learning has become a focal point of attention. However, attacks on model parameter…
FBChain: A Blockchain-based Federated Learning Model with Efficiency and Secure Communication
Yang Li, Chunhe Xia, Tianbo Wang
Privacy and security in the parameter transmission process of federated learning are currently among the most prominent concerns. However, there are two thorny problems caused by u…
HL-DPoS: An Enhanced Anti-Long-Range Attack DPoS Algorithm
Yang Li, Chunhe Xia, Chunyan Li +3
The consensus algorithm is crucial in blockchain for ensuring the validity and security of transactions across the decentralized network. However, achieving consensus among nodes a…
BRFL: A Blockchain-based Byzantine-Robust Federated Learning Model
Yang Li, Chunhe Xia, Chang Li +1
With the increasing importance of machine learning, the privacy and security of training data have become critical. Federated learning, which stores data in distributed nodes and s…