Challenging the adversarial robustness of DNNs based on error-correcting output codes

no code implementations • 26 Mar 2020 • Bowen Zhang, Benedetta Tondi, Xixiang Lv, Mauro Barni

The existence of adversarial examples and the easiness with which they can be generated raise several security concerns with regard to deep learning systems, pushing researchers to develop suitable defense mechanisms.

Adversarial Attack Adversarial Robustness +2

2P-DNN : Privacy-Preserving Deep Neural Networks Based on Homomorphic Cryptosystem

no code implementations • 23 Jul 2018 • Qiang Zhu, Xixiang Lv

We build our 2P-DNN model based on LeNet-5, and test it with the encrypted MNIST dataset.

BIG-bench Machine Learning Privacy Preserving