DLP: towards active defense against backdoor attacks with decoupled learning process
Abstract Deep learning models are well known to be susceptible to backdoor attack, where the attacker only needs to provide a tampered dataset on which the triggers are injected. Models trained on the dataset will passively implant the backdoor, and triggers on the input can mislead the models durin...
| Published in: | Cybersecurity |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2023-05-01
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| Subjects: | |
| Online Access: | https://doi.org/10.1186/s42400-023-00141-4 |