LAORAM: A Look Ahead ORAM Architecture for Training Large Embedding Tables
Authors: Rachit Rajat, Yongqin Wang, Murali Annavaram | Published: 2021-07-16 | Updated: 2022-06-30
プライバシー保護メカニズム
Towards Quantifying the Carbon Emissions of Differentially Private Machine Learning
Authors: Rakshit Naidu, Harshita Diddee, Ajinkya Mulay, Aleti Vardhan, Krithika Ramesh, Ahmed Zamzam | Published: 2021-07-14
Fedlearn-Algo: A flexible open-source privacy-preserving machine learning platform
Authors: Bo Liu, Chaowei Tan, Jiazhou Wang, Tao Zeng, Huasong Shan, Houpu Yao, Heng Huang, Peng Dai, Liefeng Bo, Yanqing Chen | Published: 2021-07-08 | Updated: 2021-07-30
Privacy Inference Attacks and Defenses in Cloud-based Deep Neural Network: A Survey
Authors: Xiaoyu Zhang, Chao Chen, Yi Xie, Xiaofeng Chen, Jun Zhang, Yang Xiang | Published: 2021-05-13
An Accuracy-Lossless Perturbation Method for Defending Privacy Attacks in Federated Learning
Authors: Xue Yang, Yan Feng, Weijun Fang, Jun Shao, Xiaohu Tang, Shu-Tao Xia, Rongxing Lu | Published: 2020-02-23 | Updated: 2021-08-15
Security and Privacy in IoT Using Machine Learning and Blockchain: Threats & Countermeasures
Authors: Nazar Waheed, Xiangjian He, Muhammad Ikram, Muhammad Usman, Saad Sajid Hashmi, Muhammad Usman | Published: 2020-02-10 | Updated: 2020-08-06
An Adaptive and Fast Convergent Approach to Differentially Private Deep Learning
Authors: Zhiying Xu, Shuyu Shi, Alex X. Liu, Jun Zhao, Lin Chen | Published: 2019-12-19
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
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