Bicoptor: Two-round Secure Three-party Non-linear Computation without Preprocessing for Privacy-preserving Machine Learning
Authors: Lijing Zhou, Ziyu Wang, Hongrui Cui, Qingrui Song, Yu Yu | Published: 2022-10-05 | Updated: 2024-04-19
DNN IP保護手法
An Embarrassingly Simple Approach for Intellectual Property Rights Protection on Recurrent Neural Networks
Authors: Zhi Qin Tan, Hao Shan Wong, Chee Seng Chan | Published: 2022-10-03 | Updated: 2022-10-04
DeltaBound Attack: Efficient decision-based attack in low queries regime
Authors: Lorenzo Rossi | Published: 2022-10-01
A Closer Look at Evaluating the Bit-Flip Attack Against Deep Neural Networks
Authors: Kevin Hector, Mathieu Dumont, Pierre-Alain Moellic, Jean-Max Dutertre | Published: 2022-09-28 | Updated: 2022-09-30
Audit and Improve Robustness of Private Neural Networks on Encrypted Data
Authors: Jiaqi Xue, Lei Xu, Lin Chen, Weidong Shi, Kaidi Xu, Qian Lou | Published: 2022-09-20
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis
Authors: Sanjay Kariyappa, Chuan Guo, Kiwan Maeng, Wenjie Xiong, G. Edward Suh, Moinuddin K Qureshi, Hsien-Hsin S. Lee | Published: 2022-09-12
Preserving Privacy in Federated Learning with Ensemble Cross-Domain Knowledge Distillation
Authors: Xuan Gong, Abhishek Sharma, Srikrishna Karanam, Ziyan Wu, Terrence Chen, David Doermann, Arun Innanje | Published: 2022-09-10
Bridging the Gap: Differentially Private Equivariant Deep Learning for Medical Image Analysis
Authors: Florian A. Hölzl, Daniel Rueckert, Georgios Kaissis | Published: 2022-09-09 | Updated: 2023-06-20
A Framework for Evaluating Privacy-Utility Trade-off in Vertical Federated Learning
Authors: Yan Kang, Jiahuan Luo, Yuanqin He, Xiaojin Zhang, Lixin Fan, Qiang Yang | Published: 2022-09-08 | Updated: 2024-08-04
Joint Linear and Nonlinear Computation across Functions for Efficient Privacy-Preserving Neural Network Inference
Authors: Qiao Zhang, Tao Xiang, Chunsheng Xin, Biwen Chen, Hongyi Wu | Published: 2022-09-04