Alternatives and similar repositories for DataLens:

Users that are interested in DataLens are comparing it to the libraries listed below

• woodyx218 / opacus_global_clipping
  ☆13Updated last year
• ksreenivasan / OOD_Federated_Learning
  ☆68Updated 2 years ago
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆30Updated 2 years ago
• pasquini-dario / SplitNN_FSHA
  Privacy attacks on Split Learning
  ☆37Updated 3 years ago
• jgshu / Attacks-and-Defenses-in-Federated-Learning
  ☆38Updated 3 years ago
• TinfoilHat0 / Defending-Against-Backdoors-with-Robust-Learning-Rate
  The code of AAAI-21 paper titled "Defending against Backdoors in Federated Learning with Robust Learning Rate".
  ☆30Updated 2 years ago
• jeremy313 / Soteria
  Official implementation of "Provable Defense against Privacy Leakage in Federated Learning from Representation Perspective"
  ☆55Updated last year
• ganeshdg95 / Leveraging-Adversarial-Examples-to-Quantify-Membership-Information-Leakage
  ☆20Updated last year
• fushuhao6 / Attack-Resistant-Federated-Learning
  ☆31Updated 4 years ago
• csong27 / property-inference-collaborative-ml
  Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
  ☆53Updated 5 years ago
• jinyuan-jia / MemGuard
  ☆45Updated 5 years ago
• dayu11 / Differentially-Private-Deep-Learning
  This repo implements several algorithms for learning with differential privacy.
  ☆104Updated 2 years ago
• AI-secure / CRFL
  CRFL: Certifiably Robust Federated Learning against Backdoor Attacks (ICML 2021)
  ☆71Updated 3 years ago
• wanglun1996 / secure-robust-federated-learning
  ☆54Updated last year
• woodyx218 / Deep-Learning-with-GDP-Pytorch
  Code to accompany the paper "Deep Learning with Gaussian Differential Privacy"
  ☆31Updated 3 years ago
• gdisag / gradient_disaggregation
  ☆14Updated last year
• DingfanChen / RelaxLoss
  Official implementation of "RelaxLoss: Defending Membership Inference Attacks without Losing Utility" (ICLR 2022)
  ☆48Updated 2 years ago
• shrezaei / MI-Attack
  ☆31Updated 5 months ago
• zlh-thu / DPFL
  A Fine-grained Differentially Private Federated Learning against Leakage from Gradients
  ☆13Updated 2 years ago
• krishnap25 / RFA
  Robust aggregation for federated learning with the RFA algorithm.
  ☆47Updated 2 years ago
• jhcknzzm / Federated-Learning-Backdoor
  ICML 2022 code for "Neurotoxin: Durable Backdoors in Federated Learning" https://arxiv.org/abs/2206.10341
  ☆68Updated last year
• krishnap25 / simplicial-fl
  Simplicial-FL to manage client device heterogeneity in Federated Learning
  ☆22Updated last year
• cpwan / Attack-Adaptive-Aggregation-in-Federated-Learning
  This is the code for our paper `Robust Federated Learning with Attack-Adaptive Aggregation' accepted by FTL-IJCAI'21.
  ☆44Updated last year
• cchoquette / membership-inference
  Code for the paper: Label-Only Membership Inference Attacks
  ☆64Updated 3 years ago
• epfml / byzantine-robust-optimizer
  Learning from history for Byzantine Robustness
  ☆22Updated 3 years ago
• JialinMao / private_CNN
  ☆10Updated 2 years ago
• OscarcarLi / label-protection
  Code Repo for paper Label Leakage and Protection in Two-party Split Learning (ICLR 2022).
  ☆23Updated 2 years ago
• s-huu / Ditto
  ☆54Updated 3 years ago
• sam-yeom / ml-privacy-csf18
  Code for the CSF 2018 paper "Privacy Risk in Machine Learning: Analyzing the Connection to Overfitting"
  ☆38Updated 6 years ago
• git-disl / CPL_attack
  ☆34Updated 3 years ago