haiphanNJIT / SecureSGDLinks
Heterogeneous Gaussian Mechanism: Preserving Differential Privacy in Deep Learning with Provable Robustness (IJCAI'19).
☆13Updated 4 years ago
Alternatives and similar repositories for SecureSGD
Users that are interested in SecureSGD are comparing it to the libraries listed below
Sorting:
- Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget☆49Updated 7 years ago
- Differential Privacy Preservation in Deep Learning under Model Attacks☆135Updated 4 years ago
- Code for the paper "Bayesian Differential Privacy for Machine Learning"☆22Updated 5 years ago
- Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…☆41Updated last year
- Implementation of calibration bounds for differential privacy in the shuffle model☆22Updated 4 years ago
- A list of papers using/about Federated Learning especially malicious client and attacks.☆12Updated 5 years ago
- Code for "Analyzing Federated Learning through an Adversarial Lens" https://arxiv.org/abs/1811.12470☆151Updated 2 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆49Updated 4 years ago
- Sample LDP implementation in Python☆129Updated 2 years ago
- This project's goal is to evaluate the privacy leakage of differentially private machine learning models.☆135Updated 2 years ago
- A sybil-resilient distributed learning protocol.☆105Updated last year
- Analytic calibration for differential privacy with Gaussian perturbations☆48Updated 6 years ago
- vertical federated learning paper lists☆76Updated 4 years ago
- 基于《A Little Is Enough: Circumventing Defenses For Distributed Learning》的联邦学习攻击模型☆64Updated 5 years ago
- An implementation of Secure Aggregation algorithm based on "Practical Secure Aggregation for Privacy-Preserving Machine Learning (Bonawit…☆88Updated 6 years ago
- Locally Private Graph Neural Networks (ACM CCS 2021)☆49Updated last month
- Federated Learning and Membership Inference Attacks experiments on CIFAR10☆22Updated 5 years ago
- Code for NDSS 2021 Paper "Manipulating the Byzantine: Optimizing Model Poisoning Attacks and Defenses Against Federated Learning"☆147Updated 3 years ago
- Curated notebooks on how to train neural networks using differential privacy and federated learning.☆68Updated 4 years ago
- reveal the vulnerabilities of SplitNN☆31Updated 3 years ago
- Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"☆33Updated 4 years ago
- The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…