Personalized federated learning (PFL) aims to produce the greatest
perso...
To defend the inference attacks and mitigate the sensitive information
l...
Self-supervised learning in computer vision trains on unlabeled data, su...
To defend the inference attacks and mitigate the sensitive information
l...
Deep Learning backdoor attacks have a threat model similar to traditiona...
We conduct a systematic study of backdoor vulnerabilities in normally tr...
Federated Learning (FL) is a distributed learning paradigm that enables
...
The attention mechanism plays a pivotal role in designing advanced
super...
Sophisticated traffic analytics, such as the encrypted traffic analytics...
Pervasive backdoors are triggered by dynamic and pervasive input
perturb...
Recent advances in single image super-resolution (SISR) have achieved
ex...
We develop a novel optimization method for NLPbackdoor inversion. We lev...
Backdoor attack injects malicious behavior to models such that inputs
em...
Back-door attack poses a severe threat to deep learning systems. It inje...
Trojan (backdoor) attack is a form of adversarial attack on deep neural
...
Deep Neural Networks (DNNs) are being used in various daily tasks such a...
Adversarial sample attacks perturb benign inputs to induce DNN misbehavi...