4 accepted papers
Model watermarking techniques can embed watermark information into the protected model for ownership declaration by constructing specific input-output pairs. However, existing watermarks are easily removed when facing model stealing attacks, and make it difficult for model owners to effectively veri
Existing ViT backdoor attacks based on backbone-overwriting full-tuning are computationally expensive and inflict performance degradation. This has forced adversaries towards the Visual Parameter-Efficient Fine-Tuning (PEFT) paradigm, dominated by adapter-based (e.g., LoRA) and prompt-based (e.g., V
Graph Contrastive Learning(GCL) is a fundamental pretraining research method in Graph Neural Networks (GNNs), which puts rich graph-level insights into the graph data to augment the data representation. However, since the existing GCLs generally regard the intra-layer node as negative samples, they…
Backdoor attack is a type of serious security threat to deep learning models.An adversary can provide users with a model trained on poisoned data to manipulate prediction behavior in test stage using a backdoor. The backdoored models behave normally on clean images, yet can be activated and output i…