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
文献データベース
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
FineFool: Fine Object Contour Attack via Attention
Authors: Jinyin Chen, Haibin Zheng, Hui Xiong, Mengmeng Su | Published: 2018-12-01
Deep Learning Application in Security and Privacy — Theory and Practice: A Position Paper
Authors: Julia A. Meister, Raja Naeem Akram, Konstantinos Markantonakis | Published: 2018-12-01
Discrete Adversarial Attacks and Submodular Optimization with Applications to Text Classification
Authors: Qi Lei, Lingfei Wu, Pin-Yu Chen, Alexandros G. Dimakis, Inderjit S. Dhillon, Michael Witbrock | Published: 2018-12-01 | Updated: 2019-04-04
Analyzing Federated Learning through an Adversarial Lens
Authors: Arjun Nitin Bhagoji, Supriyo Chakraborty, Prateek Mittal, Seraphin Calo | Published: 2018-11-29 | Updated: 2019-11-25