Guarding Machine Learning Hardware Against Physical Side-Channel Attacks
Authors: Anuj Dubey, Rosario Cammarota, Vikram Suresh, Aydin Aysu | Published: 2021-09-01
Computational Efficiency
OACAL: Finding Module-consistent Specifications to Secure Systems from Weakened User Obligations
Authors: Pengcheng Jiang, Kenji Tei | Published: 2021-08-16 | Updated: 2021-11-02
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
Certifiably Robust Interpretation via Renyi Differential Privacy
Authors: Ao Liu, Xiaoyu Chen, Sijia Liu, Lirong Xia, Chuang Gan | Published: 2021-07-04
Bayesian Attention Belief Networks
Authors: Shujian Zhang, Xinjie Fan, Bo Chen, Mingyuan Zhou | Published: 2021-06-09
Robustifying $\ell_\infty$ Adversarial Training to the Union of Perturbation Models
Authors: Ameya D. Patil, Michael Tuttle, Alexander G. Schwing, Naresh R. Shanbhag | Published: 2021-05-31 | Updated: 2021-06-11
Fed-EINI: An Efficient and Interpretable Inference Framework for Decision Tree Ensembles in Federated Learning
Authors: Xiaolin Chen, Shuai Zhou, Bei guan, Kai Yang, Hao Fan, Hu Wang, Yongji Wang | Published: 2021-05-20 | Updated: 2021-12-08
An Efficient Learning Framework For Federated XGBoost Using Secret Sharing And Distributed Optimization
Authors: Lunchen Xie, Jiaqi Liu, Songtao Lu, Tsung-hui Chang, Qingjiang Shi | Published: 2021-05-12
SIRNN: A Math Library for Secure RNN Inference
Authors: Deevashwer Rathee, Mayank Rathee, Rahul Kranti Kiran Goli, Divya Gupta, Rahul Sharma, Nishanth Chandran, Aseem Rastogi | Published: 2021-05-10
Quantifying identifiability to choose and audit $ε$ in differentially private deep learning
Authors: Daniel Bernau, Günther Eibl, Philip W. Grassal, Hannah Keller, Florian Kerschbaum | Published: 2021-03-04 | Updated: 2021-07-20