Robust and Verifiable Information Embedding Attacks to Deep Neural Networks via Error-Correcting Codes
Authors: Jinyuan Jia, Binghui Wang, Neil Zhenqiang Gong | Published: 2020-10-26
Evaluation Method
MACE: A Flexible Framework for Membership Privacy Estimation in Generative Models
Authors: Yixi Xu, Sumit Mukherjee, Xiyang Liu, Shruti Tople, Rahul Dodhia, Juan Lavista Ferres | Published: 2020-09-11 | Updated: 2022-10-12
Federated Model Distillation with Noise-Free Differential Privacy
Authors: Lichao Sun, Lingjuan Lyu | Published: 2020-09-11 | Updated: 2021-05-21
Privacy-preserving feature selection: A survey and proposing a new set of protocols
Authors: Javad Rahimipour Anaraki, Saeed Samet | Published: 2020-08-17
A Survey of Machine Learning Methods for Detecting False Data Injection Attacks in Power Systems
Authors: Ali Sayghe, Yaodan Hu, Ioannis Zografopoulos, XiaoRui Liu, Raj Gautam Dutta, Yier Jin, Charalambos Konstantinou | Published: 2020-08-16
Network Intrusion Detection Using Wrapper-based Decision Tree for Feature Selection
Authors: Mubarak Albarka Umar, Chen Zhanfang, Yan Liu | Published: 2020-08-11
How to compare adversarial robustness of classifiers from a global perspective
Authors: Niklas Risse, Christina Göpfert, Jan Philip Göpfert | Published: 2020-04-22 | Updated: 2020-10-15
Secure Evaluation of Quantized Neural Networks
Authors: Anders Dalskov, Daniel Escudero, Marcel Keller | Published: 2019-10-28 | Updated: 2021-03-01
Substra: a framework for privacy-preserving, traceable and collaborative Machine Learning
Authors: Mathieu N Galtier, Camille Marini | Published: 2019-10-25
A Note on Our Submission to Track 4 of iDASH 2019
Authors: Marcel Keller, Ke Sun | Published: 2019-10-24