DPMLBench: Holistic Evaluation of Differentially Private Machine Learning
Authors: Chengkun Wei, Minghu Zhao, Zhikun Zhang, Min Chen, Wenlong Meng, Bo Liu, Yuan Fan, Wenzhi Chen | Published: 2023-05-10 | Updated: 2023-10-14
Privacy Assessment
Differentially Private Attention Computation
Authors: Yeqi Gao, Zhao Song, Xin Yang, Yufa Zhou | Published: 2023-05-08 | Updated: 2024-10-14
Incentivising the federation: gradient-based metrics for data selection and valuation in private decentralised training
Authors: Dmitrii Usynin, Daniel Rueckert, Georgios Kaissis | Published: 2023-05-04 | Updated: 2024-04-16
GTree: GPU-Friendly Privacy-preserving Decision Tree Training and Inference
Authors: Qifan Wang, Shujie Cui, Lei Zhou, Ye Dong, Jianli Bai, Yun Sing Koh, Giovanni Russello | Published: 2023-05-01 | Updated: 2024-08-14
Private Information Retrieval and Its Applications: An Introduction, Open Problems, Future Directions
Authors: Sajani Vithana, Zhusheng Wang, Sennur Ulukus | Published: 2023-04-27
C2PI: An Efficient Crypto-Clear Two-Party Neural Network Private Inference
Authors: Yuke Zhang, Dake Chen, Souvik Kundu, Haomei Liu, Ruiheng Peng, Peter A. Beerel | Published: 2023-04-26
(Local) Differential Privacy has NO Disparate Impact on Fairness
Authors: Héber H. Arcolezi, Karima Makhlouf, Catuscia Palamidessi | Published: 2023-04-25 | Updated: 2023-08-01
Have it your way: Individualized Privacy Assignment for DP-SGD
Authors: Franziska Boenisch, Christopher Mühl, Adam Dziedzic, Roy Rinberg, Nicolas Papernot | Published: 2023-03-29 | Updated: 2024-01-19
On the Query Complexity of Training Data Reconstruction in Private Learning
Authors: Prateeti Mukherjee, Satya Lokam | Published: 2023-03-29 | Updated: 2024-01-11
XRand: Differentially Private Defense against Explanation-Guided Attacks
Authors: Truc Nguyen, Phung Lai, NhatHai Phan, My T. Thai | Published: 2022-12-08 | Updated: 2022-12-14