2 citations · 3 across the 5 of their papers we have counts for
3 papers · 1 filter
Memory Backdoor Attacks on Neural Networks
Eden Luzon, Guy Amit, Roy Weiss +3
Neural networks are often trained on proprietary datasets, making them attractive attack targets. We present a novel dataset extraction method leveraging an innovative training tim…
DNNShield: Embedding Identifiers for Deep Neural Network Ownership Verification
Jasper Stang, Torsten Krauß, Alexandra Dmitrienko
The surge in popularity of machine learning (ML) has driven significant investments in training Deep Neural Networks (DNNs). However, these models that require resource-intensive t…
CrowdGuard: Federated Backdoor Detection in Federated Learning
Phillip Rieger, Torsten Krauß, Markus Miettinen +2
Federated Learning (FL) is a promising approach enabling multiple clients to train Deep Neural Networks (DNNs) collaboratively without sharing their local training data. However, F…