5 papers
The Alignment Curse: Modality Alignment Supercharges Audio Attacks via Text Transfer
Yupeng Chen, Junchi Yu, Aoxi Liu +3
Recent advances in end-to-end trained omni-models have substantially improved audio capabilities by strengthening text-audio modality alignment. However, whether such alignment ina…
BadVideo: Stealthy Backdoor Attack against Text-to-Video Generation
Ruotong Wang, Mingli Zhu, Jiarong Ou +4
Text-to-video (T2V) generative models have rapidly advanced and found widespread applications across fields like entertainment, education, and marketing. However, the adversarial v…
Class-Conditional Neural Polarizer: A Lightweight and Effective Backdoor Defense by Purifying Poisoned Features
Mingli Zhu, Shaokui Wei, Hongyuan Zha +1
Recent studies have highlighted the vulnerability of deep neural networks to backdoor attacks, where models are manipulated to rely on embedded triggers within poisoned samples, de…
Mitigating Backdoor Attack by Injecting Proactive Defensive Backdoor
Shaokui Wei, Hongyuan Zha, Baoyuan Wu
Data-poisoning backdoor attacks are serious security threats to machine learning models, where an adversary can manipulate the training dataset to inject backdoors into models. In…
Breaking the False Sense of Security in Backdoor Defense through Re-Activation Attack
Mingli Zhu, Siyuan Liang, Baoyuan Wu
Deep neural networks face persistent challenges in defending against backdoor attacks, leading to an ongoing battle between attacks and defenses. While existing backdoor defense st…