Alternatives and similar repositories for heterogeneous-differential-privacy:

Users that are interested in heterogeneous-differential-privacy are comparing it to the libraries listed below

• McGill-DMaS / Privacy-DiffGen
  Differentially private data release for data mining [SIGKDD 2011] - convert a relational data set into a differentially-private version w…
  ☆16Updated 9 years ago
• LapisIT / differential_privacy
  QGIS differential privacy processing plugin
  ☆22Updated 8 years ago
• prashmohan / GUPT
  A Privacy Preserving Data Mining Platform
  ☆46Updated 12 years ago
• chenhongge / RobustTrees
  [ICML 2019, 20 min long talk] Robust Decision Trees Against Adversarial Examples
  ☆67Updated 2 years ago
• kohpangwei / data-poisoning-release
  ☆32Updated 7 years ago
• jagielski / manip-ml
  Code for the IEEE S&P 2018 paper 'Manipulating Machine Learning: Poisoning Attacks and Countermeasures for Regression Learning'
  ☆53Updated 3 years ago
• jinyuan-jia / AttriGuard
  ☆23Updated 6 years ago
• dpcomp-org / dpcomp_core
  ☆43Updated 3 years ago
• bargavj / distributedMachineLearning
  This work combines differential privacy and multi-party computation protocol to achieve distributed machine learning.
  ☆26Updated 4 years ago
• qiyuangong / Clustering_based_K_Anon
  cluster based generalization for k-anonymity
  ☆29Updated 5 years ago
• ninghaohello / Interpretation2Adversary
  Adversarial learning by utilizing model interpretation
  ☆10Updated 6 years ago
• BorjaBalle / analytic-gaussian-mechanism
  Analytic calibration for differential privacy with Gaussian perturbations
  ☆46Updated 6 years ago
• BielStela / membership_inference
  Python package to create adversarial agents for membership inference attacks againts machine learning models
  ☆46Updated 5 years ago
• BenKosSoft / pymovielens
  Applying differential privacy to movie recommendation system to guarantee the privacy of individual user ratings.
  ☆10Updated 7 years ago
• steven7woo / Accuracy-First-Differential-Privacy
  Code for NIPS'2017 paper
  ☆49Updated 4 years ago
• qiyuangong / Basic_Mondrian
  The raw mondrian is designed for numerical attributes. When comes to categorical attributes, Mondrian needs to transform categorical attr…
  ☆34Updated last year
• mijungi / dpem_code
  ☆8Updated 7 years ago
• houshd / TS_Adv
  Codebase for the paper "Adversarial Attacks on Time Series"
  ☆18Updated 5 years ago
• Lab41 / cyphercat
  Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …
  ☆101Updated 5 years ago
• wuyinjun-1993 / DeltaGrad
  ☆28Updated 3 years ago
• mjiang89 / LockInfer
  Inferring Strange Behavior from Connectivity Pattern (PAKDD 2014, KAIS 2015)
  ☆10Updated 9 years ago
• SummonY / DifferentialPrivacy
  Differential privacy protection based on Diffle-Hellman Key Exchange and AES256.
  ☆9Updated 9 years ago
• illidanlab / dpgan
  Source code of paper "Differentially Private Generative Adversarial Network"
  ☆68Updated 6 years ago
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆130Updated 2 years ago
• menisadi / pydp
  ☆7Updated 8 years ago
• luguoqing / Diff-FSPM
  Mining Frequent Sequential Patterns under Differential Privacy
  ☆16Updated 10 years ago
• DPBayes / dca-nips2017
  Differentially private learning on distributed data (NIPS 2017)
  ☆12Updated 7 years ago
• Raymw / Federated-XGBoost
  Federated Learning on XGBoost
  ☆46Updated 5 years ago
• SPIN-UMass / ML-Privacy-Regulization
  ☆26Updated 6 years ago
• alexandrehuat / dp-gan
  A TensorFlow (Python 3) implementation of a differentially-private-GAN.
  ☆20Updated 4 years ago