Alternatives and similar repositories for dp-promise:

Users that are interested in dp-promise are comparing it to the libraries listed below

• BorjaBalle / amplification-by-shuffling
  Implementation of calibration bounds for differential privacy in the shuffle model
  ☆23Updated 4 years ago
• caicre / PrivMRF
  An implementation of "Data Synthesis via Differentially Private Markov Random Fields"
  ☆11Updated 9 months ago
• xinjianluo / featureinference-vfl
  ☆23Updated 3 years ago
• 13thDayOfLunarMay / TECB-attack
  The implementatioin code of paper: “A Practical Clean-Label Backdoor Attack with Limited Information in Vertical Federated Learning”
  ☆11Updated last year
• facebookresearch / label_dp_antipodes
  Code to reproduce experiments in "Antipodes of Label Differential Privacy PATE and ALIBI"
  ☆30Updated 2 years ago
• chamikara1986 / LDPFL
  Local Differential Privacy for Federated Learning
  ☆16Updated 2 years ago
• shrebox / Privacy-Attacks-in-Machine-Learning
  Membership Inference, Attribute Inference and Model Inversion attacks implemented using PyTorch.
  ☆58Updated 3 months ago
• JeffffffFu / DPSUR
  DPSUR
  ☆22Updated last week
• xtLyu / CerP
  ☆13Updated 7 months ago
• zhmzm / FLAME
  ☆25Updated 11 months ago
• ppmlguy / DP-AGD
  Concentrated Differentially Private Gradient Descent with Adaptive per-iteration Privacy Budget
  ☆49Updated 6 years ago
• Guncuke / flame-Taming-backdoor
  ☆18Updated last year
• ErwinSCat / VeriFL
  IEEE TIFS'20: VeriFL: Communication-Efficient and Fast Verifiable Aggregation for Federated Learning
  ☆23Updated 2 years ago
• haoyangliASTAPLE / 3DFed
  ☆47Updated last year
• Mr-Ace-1997 / Backdoor-Attack-Against-Split-Neural-Network-Based-Vertical-Federated-Learning
  The code of the attack scheme in the paper "Backdoor Attack Against Split Neural Network-Based Vertical Federated Learning"
  ☆17Updated last year
• csong27 / property-inference-collaborative-ml
  Code for Exploiting Unintended Feature Leakage in Collaborative Learning (in Oakland 2019)
  ☆53Updated 5 years ago
• jgshu / Attacks-and-Defenses-in-Federated-Learning
  ☆38Updated 3 years ago
• zaixizhang / FLDetector
  The official code of KDD22 paper "FLDetecotor: Defending Federated Learning Against Model Poisoning Attacks via Detecting Malicious Clien…
  ☆74Updated last year
• ybdai7 / Chameleon-durable-backdoor
  [ICML 2023] Official code implementation of "Chameleon: Adapting to Peer Images for Planting Durable Backdoors in Federated Learning (htt…
  ☆37Updated 2 weeks ago
• guoJohnny / algorithmic-foundation-of-dp-zh-cn
  The Algorithmic Foundations of Differential Pivacy by Cynthia Dwork Chinese Translation
  ☆162Updated 2 years ago
• pps-lab / fl-analysis
  ☆28Updated last year
• thecml / dpsgd-optimizer
  Amortized version of the differentially private SGD algorithm published in "Deep Learning with Differential Privacy" by Abadi et al. Enfo…
  ☆41Updated 9 months ago
• purp1eHaze / FedIPR
  Webank AI
  ☆40Updated last year
• awslabs / fast-differential-privacy
  Fast, memory-efficient, scalable optimization of deep learning with differential privacy
  ☆110Updated last week
• vvv214 / LDP_Protocols
  Sample LDP implementation in Python
  ☆120Updated last year
• jinghuichen / Focused-Flip-Federated-Backdoor-Attack
  Github Repo for AAAI 2023 paper: On the Vulnerability of Backdoor Defenses for Federated Learning
  ☆35Updated last year
• dp-cont / dp-cont
  ☆13Updated 2 years ago
• anusii / graph-dp
  Implementations of differentially private release mechanisms for graph statistics
  ☆19Updated 2 years ago
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆130Updated 2 years ago
• FuChong-cyber / label-inference-attacks
  Code & supplementary material of the paper Label Inference Attacks Against Federated Learning on Usenix Security 2022.
  ☆82Updated last year