When Homomorphic Cryptosystem Meets Differential Privacy: Training Machine Learning Classifier with Privacy Protection
Authors: Xiangyun Tang, Liehuang Zhu, Meng Shen, Xiaojiang Du | Published: 2018-12-06
Differentially Private Data Generative Models
Authors: Qingrong Chen, Chong Xiang, Minhui Xue, Bo Li, Nikita Borisov, Dali Kaarfar, Haojin Zhu | Published: 2018-12-06
Calibrate: Frequency Estimation and Heavy Hitter Identification with Local Differential Privacy via Incorporating Prior Knowledge
Authors: Jinyuan Jia, Neil Zhenqiang Gong | Published: 2018-12-05 | Updated: 2018-12-11
Regularized Ensembles and Transferability in Adversarial Learning
Authors: Yifan Chen, Yevgeniy Vorobeychik | Published: 2018-12-05
Random Spiking and Systematic Evaluation of Defenses Against Adversarial Examples
Authors: Huangyi Ge, Sze Yiu Chau, Bruno Ribeiro, Ninghui Li | Published: 2018-12-05 | Updated: 2020-01-20
Outsourcing Private Machine Learning via Lightweight Secure Arithmetic Computation
Authors: Siddharth Garg, Zahra Ghodsi, Carmit Hazay, Yuval Ishai, Antonio Marcedone, Muthuramakrishnan Venkitasubramaniam | Published: 2018-12-04
Comprehensive Privacy Analysis of Deep Learning: Passive and Active White-box Inference Attacks against Centralized and Federated Learning
Authors: Milad Nasr, Reza Shokri, Amir Houmansadr | Published: 2018-12-03 | Updated: 2020-06-06
Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning
Authors: Zhibo Wang, Mengkai Song, Zhifei Zhang, Yang Song, Qian Wang, Hairong Qi | Published: 2018-12-03 | Updated: 2018-12-05
Generalization in anti-causal learning
Authors: Niki Kilbertus, Giambattista Parascandolo, Bernhard Schölkopf | Published: 2018-12-03
Model-Reuse Attacks on Deep Learning Systems
Authors: Yujie Ji, Xinyang Zhang, Shouling Ji, Xiapu Luo, Ting Wang | Published: 2018-12-02