Characterizing Membership Privacy in Stochastic Gradient Langevin Dynamics
Authors: Bingzhe Wu, Chaochao Chen, Shiwan Zhao, Cen Chen, Yuan Yao, Guangyu Sun, Li Wang, Xiaolu Zhang, Jun Zhou | Published: 2019-10-05
Privacy Protection Mechanism
PINFER: Privacy-Preserving Inference for Machine Learning
Authors: Marc Joye, Fabien A. P. Petitcolas | Published: 2019-10-04
Challenges of Privacy-Preserving Machine Learning in IoT
Authors: Mengyao Zheng, Dixing Xu, Linshan Jiang, Chaojie Gu, Rui Tan, Peng Cheng | Published: 2019-09-21
Differentially Private Regression and Classification with Sparse Gaussian Processes
Authors: Michael Thomas Smith, Mauricio A. Alvarez, Neil D. Lawrence | Published: 2019-09-19
Non-Interactive Private Decision Tree Evaluation
Authors: Anselme Tueno, Yordan Boev, Florian Kerschbaum | Published: 2019-09-18
Defending against Machine Learning based Inference Attacks via Adversarial Examples: Opportunities and Challenges
Authors: Jinyuan Jia, Neil Zhenqiang Gong | Published: 2019-09-17 | Updated: 2019-09-19
Duet: An Expressive Higher-order Language and Linear Type System for Statically Enforcing Differential Privacy
Authors: Joseph P. Near, David Darais, Chike Abuah, Tim Stevens, Pranav Gaddamadugu, Lun Wang, Neel Somani, Mu Zhang, Nikhil Sharma, Alex Shan, Dawn Song | Published: 2019-09-05
Privacy Accounting and Quality Control in the Sage Differentially Private ML Platform
Authors: Mathias Lecuyer, Riley Spahn, Kiran Vodrahalli, Roxana Geambasu, Daniel Hsu | Published: 2019-09-04 | Updated: 2019-09-06
Your Smart Home Can’t Keep a Secret: Towards Automated Fingerprinting of IoT Traffic with Neural Networks
Authors: Shuaike Dong, Zhou Li, Di Tang, Jiongyi Chen, Menghan Sun, Kehuan Zhang | Published: 2019-08-31
Privacy-preserving Distributed Machine Learning via Local Randomization and ADMM Perturbation
Authors: Xin Wang, Hideaki Ishii, Linkang Du, Peng Cheng, Jiming Chen | Published: 2019-07-30 | Updated: 2019-09-09