This work aims to tackle Model Inversion (MI) attack on Split Federated
...
Recent advancements of Deep Neural Networks (DNNs) have seen widespread
...
Neural network stealing attacks have posed grave threats to neural netwo...
Adversarial attacks on Neural Network weights, such as the progressive
b...
The wide deployment of Deep Neural Networks (DNN) in high-performance cl...
Deep Neural Network (DNN) attacks have mostly been conducted through
adv...
Robust machine learning formulations have emerged to address the prevale...
Security of machine learning is increasingly becoming a major concern du...
Security of modern Deep Neural Networks (DNNs) is under severe scrutiny ...
Deep Neural Network (DNN) trained by the gradient descent method is know...
Several important security issues of Deep Neural Network (DNN) have been...
Several important security issues of Deep Neural Network (DNN) have been...
Recent development in the field of Deep Learning have exposed the underl...
Recent studies have shown that deep neural networks (DNNs) are vulnerabl...
Deep learning algorithms and networks are vulnerable to perturbed inputs...
Deep learning algorithms and networks are vulnerable to perturbed inputs...