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05/09/2022
ResSFL: A Resistance Transfer Framework for Defending Model Inversion Attack in Split Federated Learning
This work aims to tackle Model Inversion (MI) attack on Split Federated ...
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03/09/2022
CP-ViT: Cascade Vision Transformer Pruning via Progressive Sparsity Prediction
Vision transformer (ViT) has achieved competitive accuracy on a variety ...
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12/15/2021
N3H-Core: Neuron-designed Neural Network Accelerator via FPGA-based Heterogeneous Computing Cores
Accelerating the neural network inference by FPGA has emerged as a popul...
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07/20/2021
NeurObfuscator: A Full-stack Obfuscation Tool to Mitigate Neural Architecture Stealing
Neural network stealing attacks have posed grave threats to neural netwo...
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03/02/2021
SME: ReRAM-based Sparse-Multiplication-Engine to Squeeze-Out Bit Sparsity of Neural Network
Resistive Random-Access-Memory (ReRAM) crossbar is a promising technique...
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01/20/2021
RADAR: Run-time Adversarial Weight Attack Detection and Accuracy Recovery
Adversarial attacks on Neural Network weights, such as the progressive b...
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07/24/2020
T-BFA: Targeted Bit-Flip Adversarial Weight Attack
Deep Neural Network (DNN) attacks have mostly been conducted through adv...
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09/10/2019
TBT: Targeted Neural Network Attack with Bit Trojan
Security of modern Deep Neural Networks (DNNs) is under severe scrutiny ...
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07/03/2019
Non-structured DNN Weight Pruning Considered Harmful
Large deep neural network (DNN) models pose the key challenge to energy ...
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05/30/2019
Robust Sparse Regularization: Simultaneously Optimizing Neural Network Robustness and Compactness
Deep Neural Network (DNN) trained by the gradient descent method is know...
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03/28/2019
Bit-Flip Attack: Crushing Neural Network with Progressive Bit Search
Several important security issues of Deep Neural Network (DNN) have been...
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03/28/2019
Bit-Flip Attack: Crushing Neural Network withProgressive Bit Search
Several important security issues of Deep Neural Network (DNN) have been...
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11/22/2018
Parametric Noise Injection: Trainable Randomness to Improve Deep Neural Network Robustness against Adversarial Attack
Recent development in the field of Deep Learning have exposed the underl...
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10/02/2018
Simultaneously Optimizing Weight and Quantizer of Ternary Neural Network using Truncated Gaussian Approximation
In the past years, Deep convolution neural network has achieved great su...
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07/20/2018
Optimize Deep Convolutional Neural Network with Ternarized Weights and High Accuracy
Deep convolution neural network has achieved great success in many artif...
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02/05/2018
Blind Pre-Processing: A Robust Defense Method Against Adversarial Examples
Deep learning algorithms and networks are vulnerable to perturbed inputs...
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02/05/2018
Robust Pre-Processing: A Robust Defense Method Against Adversary Attack
Deep learning algorithms and networks are vulnerable to perturbed inputs...
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05/08/2017
