Privacy Risks of Securing Machine Learning Models against Adversarial Examples
Authors: Liwei Song, Reza Shokri, Prateek Mittal | Published: 2019-05-24 | Updated: 2019-08-25
Partially Encrypted Machine Learning using Functional Encryption
Authors: Theo Ryffel, Edouard Dufour-Sans, Romain Gay, Francis Bach, David Pointcheval | Published: 2019-05-24 | Updated: 2021-09-23
Power up! Robust Graph Convolutional Network via Graph Powering
Authors: Ming Jin, Heng Chang, Wenwu Zhu, Somayeh Sojoudi | Published: 2019-05-24 | Updated: 2021-09-21
Robust Attribution Regularization
Authors: Jiefeng Chen, Xi Wu, Vaibhav Rastogi, Yingyu Liang, Somesh Jha | Published: 2019-05-23 | Updated: 2019-10-26
Thwarting finite difference adversarial attacks with output randomization
Authors: Haidar Khan, Daniel Park, Azer Khan, Bülent Yener | Published: 2019-05-23
Adversarially Robust Distillation
Authors: Micah Goldblum, Liam Fowl, Soheil Feizi, Tom Goldstein | Published: 2019-05-23 | Updated: 2019-12-02
A Direct Approach to Robust Deep Learning Using Adversarial Networks
Authors: Huaxia Wang, Chun-Nam Yu | Published: 2019-05-23
Deep Reinforcement Learning for Detecting Malicious Websites
Authors: Moitrayee Chatterjee, Akbar Siami Namin | Published: 2019-05-22
A framework for the extraction of Deep Neural Networks by leveraging public data
Authors: Soham Pal, Yash Gupta, Aditya Shukla, Aditya Kanade, Shirish Shevade, Vinod Ganapathy | Published: 2019-05-22
Learning to Confuse: Generating Training Time Adversarial Data with Auto-Encoder
Authors: Ji Feng, Qi-Zhi Cai, Zhi-Hua Zhou | Published: 2019-05-22