Papers with online defense methods
Expose Backdoors on the Way: A Feature-Based Efficient Defense against Textual Backdoor Attacks (2022.findings-emnlp)
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| Challenge: | Existing online backdoor defense methods for NLP models focus on anomalies at input or output level, causing fragility to adaptive attacks and high computational cost. |
| Approach: | They propose a feature-based online defense method to detect poisoned samples . they use a distance-based anomaly score to distinguish poisones from clean samples based on feature-level regularization . |
| Outcome: | The proposed method outperforms existing methods in sentiment analysis and offense detection tasks. |
RAP: Robustness-Aware Perturbations for Defending against Backdoor Attacks on NLP Models (2021.emnlp-main)
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| Challenge: | Backdoor attacks are a serious threat to the safety of reusing deep neural networks (DNNs). |
| Approach: | They propose an efficient online defense mechanism based on robustness-aware perturbations to distinguish poisoned and clean samples to defend against backdoor attacks on natural language processing models. |
| Outcome: | The proposed method achieves better defending performance and lower computational costs than existing defense methods. |