Backdoor defense method in federated learning based on contrastive training [PDF]
In response to the inadequacy of existing defense methods for backdoor attacks in federated learning to effectively remove embedded backdoor features from models, while simultaneously reducing the accuracy of the primary task, a federated learning ...
Bing CHEN +4 more
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Adaptive clustering federated learning via similarity acceleration [PDF]
In order to solve the problem of model performance degradation caused by data heterogeneity in the federated learning process, it is necessary to consider personalizing in the federated model.A new adaptively clustering federated learning (ACFL ...
Binke GU, Guanglu SUN, Suxia ZHU
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Joint multi-dimensional resource optimization for model compression in wireless federated learning [PDF]
In the edge computing scenarios, resource-constrained and particiption of the dynamically terminal devices of network in federated learning cause high latency and high energy consumption.
XU Ding, ZHU Guangzhao, ZHU Xiaorong
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Dual-Client Selection Algorithm Based on Model Similarity and Local Loss [PDF]
Federated learning is a distributed machine-learning technique that collaboratively constructs a global model by aggregating local model parameters from clients.
Hongjiao LI, Baojin WANG, Zhaohui WANG, Renhao HU
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Cloud-Edge Fusion Verifiable Privacy-Preserving Cross-Domain Federated Learning Scheme [PDF]
The rapid development of Federated Learning(FL) technology promotes collaborative training of gradient models using data from different end users. Its notable feature is that the training dataset does not leave the local device, and only gradient model ...
Xiaojun ZHANG, Xingpeng LI, Wei TANG, Yunpu HAO, Jingting XUE
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Secure federated learning scheme based on adaptive Byzantine defense [PDF]
Aiming at the problem that the existing federated learning schemes cannot adaptively defend Byzantine attacks and low model accuracy, a secure federated learning scheme based on adaptive Byzantine defense was proposed.
GAO Jingkun +3 more
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Multi-Technology Fused Data Trading Method Based on Federated Learning [PDF]
The constraints of data protection have restricted data within different enterprises and organizations, forming several "data islands" that make it difficult to tap into their inherent important value.
Shaojie LIU, Bin WEN, Zexu WANG
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Ship AIS Trajectory Prediction Algorithm Based on Federated Learning [PDF]
Federated learning, a distributed machine learning method, effectively addresses the data island problem in environments with weak communication. This study introduces an algorithm for predicting ship trajectories, employing the Fedves federated learning
Chenjun ZHENG, Yan ZENG, Junfeng YUAN, Jilin ZHANG, Xin WANG, Meng HAN
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Research on distributed network intrusion detection system for IoT based on honeyfarm [PDF]
To solve the problems that the network intrusion detection system in the Internet of things couldn’t identify new attacks and has limited flexibility, a network intrusion detection system based on honeyfarm was proposed, which could effectively identify ...
Hao WU, Jiajia HAO, Yunlong LU
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Client selection for federated learning against label flipping attacks [PDF]
Federated learning (FL) allows multiple clients to train a global model collaboratively by sharing only model updates without uploading local data. But due to its distributed global aggregation mode, FL is vulnerable to the malicious impact of label ...
CHEN Siguang, LI Jianxin
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