AIDFL: An Information-Driven Anomaly Detector for Data Poisoning in Decentralized Federated Learning
Decentralized Federated Learning eliminates central servers by enabling direct communication among clients. However, this structure introduces significant security challenges, as each client has access to the model parameters. Existing defense mechanisms face significantly reduced effectiveness unde...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10930423/ |
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