Papers with black-box attack method
Adv-OLM: Generating Textual Adversaries via OLM (2021.eacl-main)
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| Challenge: | Recent studies have pointed out the vulnerability of deep learning models to adversarial attacks. |
| Approach: | They propose a black-box attack method that adapts the idea of Occlusion and Language Models to the current state of the art attack methods. |
| Outcome: | The proposed method outperforms existing methods on several text classification tasks. |
Crafting Adversarial Examples for Neural Machine Translation (2021.acl-long)
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| Challenge: | Effective adversary generation for neural machine translation is crucial for robust systems. |
| Approach: | They propose to leverage round-trip translation technique to build valid metrics for evaluating NMT adversarial attacks. |
| Outcome: | The proposed method could break the state-of-art NMT models with small perturbations. |
DIP: Dead code Insertion based Black-box Attack for Programming Language Model (2023.acl-long)
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| Challenge: | Existing methods to attack natural language models are difficult to apply due to the requirements. |
| Approach: | They propose a black-box attack method that generates adversarial examples using dead code insertion. |
| Outcome: | The proposed method outperforms the state-of-the-art black-box attack in both attack efficiency and attack quality on 9 victim downstream-task large code models. |