A sparse and invisible targeted backdoor attack in federated learning
Abstract In distributed edge Computing scenarios within the Internet of Things (IoT), individual clients are susceptible to adversarial backdoor attacks, wherein malicious modifications to local data may be introduced. Such compromised clients can negatively impact the integrity and performance of t...
| Published in: | Journal of King Saud University: Computer and Information Sciences |
|---|---|
| Main Authors: | , , , , , |
| Format: | Article |
| Language: | English |
| Published: |
Springer
2025-07-01
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| Subjects: | |
| Online Access: | https://doi.org/10.1007/s44443-025-00146-8 |
