Defending Against Backdoor Attacks by Quarantine Training
Deep neural networks (DNNs) are powerful yet vulnerable to backdoor attacks simply by adding backdoor samples to the training set without controlling the training process. To filter out the backdoor samples in the training set, this paper proposes a novel and effective backdoor defense method called...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10400485/ |