37 citations · 58 across the 9 of their papers we have counts for
4 papers · 1 filter
Backdoor Attacks on Transformers for Tabular Data: An Empirical Study
Bart Pleiter, Behrad Tajalli, Stefanos Koffas +4
Deep Neural Networks (DNNs) have shown great promise in various domains. However, vulnerabilities associated with DNN training, such as backdoor attacks, are a significant concern.…
Label-Only Membership Inference Attack against Node-Level Graph Neural Networks
Mauro Conti, Jiaxin Li, Stjepan Picek +1
Graph Neural Networks (GNNs), inspired by Convolutional Neural Networks (CNNs), aggregate the message of nodes' neighbors and structure information to acquire expressive representa…
More is Better (Mostly): On the Backdoor Attacks in Federated Graph Neural Networks
Jing Xu, Rui Wang, Stefanos Koffas +2
Graph Neural Networks (GNNs) are a class of deep learning-based methods for processing graph domain information. GNNs have recently become a widely used graph analysis method due t…
Can You Hear It? Backdoor Attacks via Ultrasonic Triggers
Stefanos Koffas, Jing Xu, Mauro Conti +1
This work explores backdoor attacks for automatic speech recognition systems where we inject inaudible triggers. By doing so, we make the backdoor attack challenging to detect for…