Alternatives and similar repositories for PrivacyRaven

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

• unica-mlsec / mlsec
  PhD/MSc course on Machine Learning Security (Univ. Cagliari)
  ☆212Updated 3 months ago
• twosixlabs / armory
  ARMORY Adversarial Robustness Evaluation Test Bed
  ☆184Updated last year
• stratosphereips / awesome-ml-privacy-attacks
  An awesome list of papers on privacy attacks against machine learning
  ☆624Updated last year
• Lab41 / cyphercat
  Implementation of membership inference and model inversion attacks, extracting training data information from an ML model. Benchmarking …
  ☆103Updated 5 years ago
• pralab / secml
  A Python library for Secure and Explainable Machine Learning
  ☆186Updated 2 months ago
• privacytrustlab / ml_privacy_meter
  Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.
  ☆678Updated 4 months ago
• google-research / selfstudy-adversarial-robustness
  ☆128Updated 3 years ago
• trojai / trojai
  A repository to quickly generate synthetic data and associated trojaned deep learning models
  ☆81Updated 2 years ago
• spring-epfl / mia
  A library for running membership inference attacks against ML models
  ☆149Updated 2 years ago
• google-research / cryptanalytic-model-extraction
  ☆54Updated 4 years ago
• nesl / nist_differential_privacy_synthetic_data_challenge
  UCLANesl - NIST Differential Privacy Challenge (Match 3)
  ☆25Updated 6 years ago
• jeiks / Stealing_DL_Models
  Copycat CNN
  ☆27Updated last year
• microsoft / msrflute
  Federated Learning Utilities and Tools for Experimentation
  ☆190Updated last year
• spring-epfl / synthetic_data_release
  ☆40Updated 2 years ago
• mortendahl / awesome-ppml
  A curated list of resources for privacy-preserving machine learning
  ☆149Updated 3 years ago
• sunblaze-ucb / dpml-benchmark
  This repository contains the codes for first large-scale investigation of Differentially Private Convex Optimization algorithms.
  ☆63Updated 6 years ago
• yuxiangw / autodp
  autodp: A flexible and easy-to-use package for differential privacy
  ☆275Updated last year
• usnistgov / trojai-literature
  ☆147Updated 11 months ago
• mmalekzadeh / honest-but-curious-nets
  Honest-but-Curious Nets: Sensitive Attributes of Private Inputs Can Be Secretly Coded into the Classifiers' Outputs (ACM CCS'21)
  ☆17Updated 2 years ago
• ebagdasa / backdoors101
  Backdoors Framework for Deep Learning and Federated Learning. A light-weight tool to conduct your research on backdoors.
  ☆371Updated 2 years ago
• cleverhans-lab / capc-iclr
  CaPC is a method that enables collaborating parties to improve their own local heterogeneous machine learning models in a setting where b…
  ☆26Updated 3 years ago
• bargavj / EvaluatingDPML
  This project's goal is to evaluate the privacy leakage of differentially private machine learning models.
  ☆136Updated 2 years ago
• OpenMined / PyDP
  The Python Differential Privacy Library. Built on top of: https://github.com/google/differential-privacy
  ☆531Updated last year
• ZhengyuZhao / AI-Security-and-Privacy-Events
  A curated list of academic events on AI Security & Privacy
  ☆162Updated last year
• inspire-group / membership-inference-evaluation
  Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models
  ☆127Updated last year
• OpenMined / SyMPC
  A SMPC companion library for Syft
  ☆104Updated 2 months ago
• trx14 / TrojanNet
  ☆87Updated last year
• IBM / URET
  Universal Robustness Evaluation Toolkit (for Evasion)
  ☆31Updated 4 months ago
• opendp / smartnoise-sdk
  Tools and service for differentially private processing of tabular and relational data
  ☆280Updated last month
• Azure / 2021-machine-learning-security-evasion-competition
  ☆19Updated 4 years ago