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
プライバシー手法
Reconstruction of Privacy-Sensitive Data from Protected Templates
Authors: Shideh Rezaeifar, Behrooz Razeghi, Olga Taran, Taras Holotyak, Slava Voloshynovskiy | Published: 2019-05-08
Privacy-Preserving Deep Neural Networks with Pixel-based Image Encryption Considering Data Augmentation in the Encrypted Domain
Authors: Warit Sirichotedumrong, Takahiro Maekawa, Yuma Kinoshita, Hitoshi Kiya | Published: 2019-05-06
Locally Differentially Private Naive Bayes Classification
Authors: Emre Yilmaz, Mohammad Al-Rubaie, J. Morris Chang | Published: 2019-05-03
Performing Co-Membership Attacks Against Deep Generative Models
Authors: Kin Sum Liu, Chaowei Xiao, Bo Li, Jie Gao | Published: 2018-05-24 | Updated: 2019-09-20
Generating Artificial Data for Private Deep Learning
Authors: Aleksei Triastcyn, Boi Faltings | Published: 2018-03-08 | Updated: 2019-04-28
Scalable Private Learning with PATE
Authors: Nicolas Papernot, Shuang Song, Ilya Mironov, Ananth Raghunathan, Kunal Talwar, Úlfar Erlingsson | Published: 2018-02-24
Context-Aware Generative Adversarial Privacy
Authors: Chong Huang, Peter Kairouz, Xiao Chen, Lalitha Sankar, Ram Rajagopal | Published: 2017-10-26 | Updated: 2017-12-03
Desensitized RDCA Subspaces for Compressive Privacy in Machine Learning
Authors: Artur Filipowicz, Thee Chanyaswad, S. Y. Kung | Published: 2017-07-24