Reducing Risk of Model Inversion Using Privacy-Guided Training
Authors: Abigail Goldsteen, Gilad Ezov, Ariel Farkash | Published: 2020-06-29
モデルインバージョン
Stealing Links from Graph Neural Networks
Authors: Xinlei He, Jinyuan Jia, Michael Backes, Neil Zhenqiang Gong, Yang Zhang | Published: 2020-05-05 | Updated: 2020-10-05
Attacking Graph-based Classification via Manipulating the Graph Structure
Authors: Binghui Wang, Neil Zhenqiang Gong | Published: 2019-03-01 | Updated: 2019-08-13
AutoGAN-based Dimension Reduction for Privacy Preservation
Authors: Hung Nguyen, Di Zhuang, Pei-Yuan Wu, Morris Chang | Published: 2019-02-27 | Updated: 2021-07-27
Adversarial Neural Network Inversion via Auxiliary Knowledge Alignment
Authors: Ziqi Yang, Ee-Chien Chang, Zhenkai Liang | Published: 2019-02-22
Privacy Partitioning: Protecting User Data During the Deep Learning Inference Phase
Authors: Jianfeng Chi, Emmanuel Owusu, Xuwang Yin, Tong Yu, William Chan, Patrick Tague, Yuan Tian | Published: 2018-12-07
Differentially Private Data Generative Models
Authors: Qingrong Chen, Chong Xiang, Minhui Xue, Bo Li, Nikita Borisov, Dali Kaarfar, Haojin Zhu | Published: 2018-12-06
Generalised Differential Privacy for Text Document Processing
Authors: Natasha Fernandes, Mark Dras, Annabelle McIver | Published: 2018-11-26 | Updated: 2019-02-05
Excessive Invariance Causes Adversarial Vulnerability
Authors: Jörn-Henrik Jacobsen, Jens Behrmann, Richard Zemel, Matthias Bethge | Published: 2018-11-01 | Updated: 2020-07-12
Adversarial Attacks and Defences: A Survey
Authors: Anirban Chakraborty, Manaar Alam, Vishal Dey, Anupam Chattopadhyay, Debdeep Mukhopadhyay | Published: 2018-09-28