Defending Deep Neural Networks Against Backdoor Attack by Using De-Trigger Autoencoder
A backdoor attack is a method that causes misrecognition in a deep neural network by training it on additional data that have a specific trigger. The network will correctly recognize normal samples (which lack the specific trigger) as their proper classes but will misrecognize backdoor samples (whic...
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| Main Author: | |
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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/9579062/ |
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