14 citations · 45 across the 14 of their papers we have counts for
4 papers · 1 filter
EdgePruner: Poisoned Edge Pruning in Graph Contrastive Learning
Hiroya Kato, Kento Hasegawa, Seira Hidano +1
Graph Contrastive Learning (GCL) is unsupervised graph representation learning that can obtain useful representation of unknown nodes. The node representation can be utilized as fe…
Magmaw: Modality-Agnostic Adversarial Attacks on Machine Learning-Based Wireless Communication Systems
Jung-Woo Chang, Ke Sun, Nasimeh Heydaribeni +3
Machine Learning (ML) has been instrumental in enabling joint transceiver optimization by merging all physical layer blocks of the end-to-end wireless communication systems. Althou…
VoteTRANS: Detecting Adversarial Text without Training by Voting on Hard Labels of Transformations
Hoang-Quoc Nguyen-Son, Seira Hidano, Kazuhide Fukushima +2
Adversarial attacks reveal serious flaws in deep learning models. More dangerously, these attacks preserve the original meaning and escape human recognition. Existing methods for d…
NetFlick: Adversarial Flickering Attacks on Deep Learning Based Video Compression
Jung-Woo Chang, Nojan Sheybani, Shehzeen Samarah Hussain +3
Video compression plays a significant role in IoT devices for the efficient transport of visual data while satisfying all underlying bandwidth constraints. Deep learning-based vide…