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Nguyen Hung-Quang

3 accepted papers

2025

Wicked Oddities: Selectively Poisoning for Effective Clean-Label Backdoor Attacks

ICLR 2025poster

Deep neural networks are vulnerable to backdoor attacks, a type of adversarial attack that poisons the training data to manipulate the behavior of models trained on such data. Clean-label backdoor is a more stealthy form of backdoor attacks that can perform the attack without changing the labels of…

Cited by 2SourcePDFScholar
2024

Fooling the Textual Fooler via Randomizing Latent Representations

ACL 2024findings

Despite outstanding performance in a variety of Natural Language Processing (NLP) tasks, recent studies have revealed that NLP models are vulnerable to adversarial attacks that slightly perturb the input to cause the models to misbehave. Several attacks can even compromise the model without requirin…

Cited by 0SourcePDFScholar
2024

Understanding the Robustness of Randomized Feature Defense Against Query-Based Adversarial Attacks

ICLR 2024poster

Recent works have shown that deep neural networks are vulnerable to adversarial examples that find samples close to the original image but can make the model misclassify. Even with access only to the model's output, an attacker can employ black-box attacks to generate such adversarial examples. In t…