This work aims to tackle Model Inversion (MI) attack on Split Federated
...
Vision transformer (ViT) has achieved competitive accuracy on a variety ...
Accelerating the neural network inference by FPGA has emerged as a popul...
Neural network stealing attacks have posed grave threats to neural netwo...
Resistive Random-Access-Memory (ReRAM) crossbar is a promising technique...
Adversarial attacks on Neural Network weights, such as the progressive
b...
Deep Neural Network (DNN) attacks have mostly been conducted through
adv...
Security of modern Deep Neural Networks (DNNs) is under severe scrutiny ...
Large deep neural network (DNN) models pose the key challenge to energy
...
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...
In the past years, Deep convolution neural network has achieved great su...
Deep convolution neural network has achieved great success in many artif...
Deep learning algorithms and networks are vulnerable to perturbed inputs...
Deep learning algorithms and networks are vulnerable to perturbed inputs...
In this work, we have proposed a revolutionary neuromorphic computing
me...