privacy-security Goto Github PK

adversarial-robustness-toolbox

Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference

aiops

anomalydetection

Anomaly Detection with R

awesome-he

✨ Awesome - A curated list of amazing Homomorphic Encryption libraries, software and resources

awesome-ml-privacy-attacks

An awesome list of papers on privacy attacks against machine learning

cleverhans

An adversarial example library for constructing attacks, building defenses, and benchmarking both

concrete-ml

Concrete-ML: A library to turn machine learning models into their homomorphic equivalent.

courses

A place where our community can discuss OpenMined Courses, including posting questions, sharing feedback, or providing comments for discussion!

crypten

A framework for Privacy Preserving Machine Learning

cybertweets

annotated dataset of cyber-security related tweets

data-synthesis-for-machine-learning

Synthesize a new dataset based on the original dataset for later machine learning to facilitate the data sharing from the customer.

differential-privacy

Google's differential privacy library.

efficient-gan-anomaly-detection

fate

An Industrial Grade Federated Learning Framework

federated-learning-lib

A library for federated learning (a distributed machine learning process) in an enterprise environment.

flow-forecast

Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).

flower

Flower - A Friendly Federated Learning Framework

flsim

Federated Learning Simulator (FLSim) is a flexible, standalone core library that simulates FL settings with a minimal, easy-to-use API. FLSim is domain-agnostic and accommodates many use cases such as vision and text.

graph-neural-networks

GNN implementations with PyG

id2t

Official ID2T repository. ID2T creates labeled IT network datasets that contain user defined synthetic attacks.

lime-1

LiME (formerly DMD) is a Loadable Kernel Module (LKM), which allows the acquisition of volatile memory from Linux and Linux-based devices, such as those powered by Android. The tool supports acquiring memory either to the file system of the device or over the network. LiME is unique in that it is the first tool that allows full memory captures from Android devices. It also minimizes its interaction between user and kernel space processes during acquisition, which allows it to produce memory captures that are more forensically sound than those of other tools designed for Linux memory acquisition.

malware-gems

A not so awesome list of malware gems for aspiring malware analysts

ml_privacy_meter

Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.

nab

The Numenta Anomaly Benchmark

network-threats-taxonomy

Machine Learning based Intrusion Detection Systems are difficult to evaluate due to a shortage of datasets representing accurately network traffic and their associated threats. In this project we attempt at solving this problem by presenting two taxonomies

opacus

Training PyTorch models with differential privacy

practical-cryptography-in-python

Source code for 'Cryptography in Python Source Code' by Seth Nielson and Christopher K. Monson

programming-dp

pydbgen

Random dataframe and database table generator

pysynth

Synthesize datasets in Python.