Papers with textual backdoor attacks

3 papers
Hidden Killer: Invisible Textual Backdoor Attacks with Syntactic Trigger (2021.acl-long)

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Challenge: Existing methods for textual backdoor attacks insert additional contents into normal samples as triggers, causing detection and blocking of backdoors.
Approach: They propose to use syntactic structure as trigger in textual backdoor attacks . they propose to achieve similar attack performance but have higher invisibility .
Outcome: The proposed method achieves almost 100% success rate but has higher invisibility and stronger resistance to defenses than the insertion-based methods.
PKAD: Pretrained Knowledge is All You Need to Detect and Mitigate Textual Backdoor Attacks (2024.findings-emnlp)

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Challenge: Current defense methods can be classified into inference-time and training-time ones based on their execution phase.
Approach: They propose a two-stage poison detection strategy using pre-trained language models to detect poisoned samples before model training.
Outcome: The proposed method achieves better performance than current methods more quickly and with fewer training costs.
Prompt as Triggers for Backdoor Attack: Examining the Vulnerability in Language Models (2023.emnlp-main)

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Challenge: ProAttack is a novel and efficient method for performing clean-label backdoor attacks based on the prompt, which uses the prompt itself as a trigger.
Approach: They propose a method for performing clean-label backdoor attacks based on the prompt, which uses the prompt itself as a trigger.
Outcome: The proposed method achieves state-of-the-art performance on several NLP tasks, particularly in few-shot settings.

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