garrisongys Goto Github PK

adversarial-mtsr

AE on time-series regression model

adversarial-robustness-toolbox

This is a library dedicated to adversarial machine learning. Its purpose is to allow rapid crafting and analysis of attacks and defense methods for machine learning models. The Adversarial Robustness Toolbox provides an implementation for many state-of-the-art methods for attacking and defending classifiers. https://developer.ibm.com/code/open/projects/adversarial-robustness-toolbox/

backdoor-learning-resources

A curated list of backdoor learning resources

badnets

bnn

casestudy

dba

DBA: Distributed Backdoor Attacks against Federated Learning

deeplearning

deeplearning-cats-dogs-tutorial

Source code for blog post: A Practical Introduction to Deep Learning with Caffe and Python

deeprobust

A pytorch adversarial library for attack and defense methods on images and graphs

federated-learning-and-split-learning-with-raspberry-pi

SRDS 2020: End-to-End Evaluation of Federated Learning and Split Learning for Internet of Things

gans-awesome-applications

Curated list of awesome GAN applications and demo

garrison

Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes

green-energy-production-inverter-prediction

The project aims to use AI to improve the prediction of weather and equipment failure in order to optimize power generation from solar panels.

learngit

localuploadtest

machine-learning-collection

Traditional Machine Learning and Deeplearning using Pytorch

malnet-image

A large-scale database of malicious software images

mesapy

A Fast and Safe Python based on PyPy

notes

my dev notes

pypuf

Cryptanalysis of Physically Unclonable Functions

pysyft

A library for encrypted, privacy preserving deep learning

python-fuzzy-extractor

A Python implementation of fuzzy extractor.

pythoncrypto

relu_defense

ReLU defense against adversarial attacks

simple_adversarial_examples

Repo of simple adversarial examples on vanilla neural networks trained on MNIST

smoothing

Provable adversarial robustness at ImageNet scale

splitfed

strip

This is for releasing the source code of the ACSAC paper "STRIP: A Defence Against Trojan Attacks on Deep Neural Networks"

stux-dnn

Run-time trojan attack on neural networks