3篇
您的检索式：作者名="HE Benteng"
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| 1 | A new method to identify inrush current based on error estimation显示文摘 | HE Benteng ZHANG Xuesong BO Zhiqian | 2006 | IEEE Transactions on Power Delivery2006，21，3： | 1 |
| 2 | An adaptive distance relay based on transient error estimation ofCVT显示文摘 | He Benteng Li Yiquan Bo Z Q | 2006 | IEEE Transactions on Power Delivery2006，21，4： | 1 |
| 3 | Improving Federated Learning through Abnormal Client Detection and Incentive显示文摘Data sharing and privacy protection are made possible by federated learning,which allows for continuous model parameter sharing between several clients and a central server.Multiple reliable and high-quality clients must participate in practical applications for the federated learning global model to be accurate,but because the clients are independent,the central server cannot fully control their behavior.The central server has no way of knowing the correctness of the model parameters provided by each client in this round,so clients may purposefully or unwittingly submit anomalous data,leading to abnormal behavior,such as becoming malicious attackers or defective clients.To reduce their negative consequences,it is crucial to quickly detect these abnormalities and incentivize them.In this paper,we propose a Federated Learning framework for Detecting and Incentivizing Abnormal Clients(FL-DIAC)to accomplish efficient and security federated learning.We build a detector that introduces an auto-encoder for anomaly detection and use it to perform anomaly identification and prevent the involvement of abnormal clients,in particular for the anomaly client detection problem.Among them,before the model parameters are input to the detector,we propose a Fourier transform-based anomaly data detectionmethod for dimensionality reduction in order to reduce the computational complexity.Additionally,we create a credit scorebased incentive structure to encourage clients to participate in training in order tomake clients actively participate.Three training models(CNN,MLP,and ResNet-18)and three datasets(MNIST,Fashion MNIST,and CIFAR-10)have been used in experiments.According to theoretical analysis and experimental findings,the FL-DIAC is superior to other federated learning schemes of the same type in terms of effectiveness. | Hongle Guo Yingchi Mao Xiaoming He Benteng Zhang Tianfu Pang Ping Ping | 2024 | Computer Modeling in Engineering & Sciences2024，139，4： | 0 |
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