5 papers
Time Is All It Takes: Spike-Retiming Attacks on Event-Driven Spiking Neural Networks
Yi Yu, Qixin Zhang, Shuhan Ye +6
Spiking neural networks (SNNs) compute with discrete spikes and exploit temporal structure, yet most adversarial attacks change intensities or event counts instead of timing. We st…
StegaVAR: Privacy-Preserving Video Action Recognition via Steganographic Domain Analysis
Lixin Chen, Chaomeng Chen, Jiale Zhou +2
Despite the rapid progress of deep learning in video action recognition (VAR) in recent years, privacy leakage in videos remains a critical concern. Current state-of-the-art privac…
Transferable Adversarial Attacks on SAM and Its Downstream Models
Song Xia, Wenhan Yang, Yi Yu +4
The utilization of large foundational models has a dilemma: while fine-tuning downstream tasks from them holds promise for making use of the well-generalized knowledge in practical…
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation
Yi Yu, Song Xia, Xun Lin +5
Adversarial examples, characterized by imperceptible perturbations, pose significant threats to deep neural networks by misleading their predictions. A critical aspect of these exa…
Backdoor Attacks against No-Reference Image Quality Assessment Models via a Scalable Trigger
Yi Yu, Song Xia, Xun Lin +4
No-Reference Image Quality Assessment (NR-IQA), responsible for assessing the quality of a single input image without using any reference, plays a critical role in evaluating and o…