522539291

GAN-AD

We used generative adversarial networks (GANs) to do anomaly detection for time series data.

advGAN_pytorch

a Pytorch implementation of the paper "Generating Adversarial Examples with Adversarial Networks" (advGAN).

ADD-GAN

Anomaly Detection Discriminative GAN (ADD-GAN)

All-About-the-GAN

All About the GANs(Generative Adversarial Networks) - Summarized lists for GAN

Semi-Supervised-Learning-GAN

Semi-supervised Learning GAN

APE-GAN

Tensorflow implementation of Our APE-GAN

MAD-GANs

Applied generative adversarial networks (GANs) to do anomaly detection for time series data

kdd99-scikit

Solutions to kdd99 dataset with Decision tree and Neural network by scikit-learn

Network-Intrusion-Detection-Using-Machine-Learning-Techniques

Network intrusions classification using algorithms such as Support Vector Machine (SVM), Decision Tree, Naive Baye, K-Nearest Neighbor (KNN), Logistic Regression and Random Forest.

nsl-kdd

PySpark solution to the NSL-KDD dataset: https://www.unb.ca/cic/datasets/nsl.html

Mastering-Machine-Learning-for-Penetration-Testing

Mastering Machine Learning for Penetration Testing, published by Packt

cifar-vgg

VGG16 models for CIFAR-10 and CIFAR-100 using Keras

AI_Security

This is a paper list about Machine Learning for IDSes

Intrusion-Detection-Systems

This is the repo of the research paper, "Evaluating Shallow and Deep Neural Networks for Network Intrusion Detection Systems in Cyber Security".

IDS-UNSW-NB15

IoT intrusion Detection Model based on neural network and random forests

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

APTSimulator

A toolset to make a system look as if it was the victim of an APT attack

replication_arxiv_1805_03735

Replication files for arXiv:1805.03735 Sequence Aggregation Rules for Anomaly Detection in Computer Network Traffic

DeepTraffic

Deep Learning models for network traffic classification

TCPDUMP_and_CICFlowMeter

These scripts conduct TCPDUMP in harmony with CICFlowMeter to operation real-time traffic capturing and converting in csv file.

PcapPlusPlus

PcapPlusPlus is a multiplatform C++ library for capturing, parsing and crafting of network packets. It is designed to be efficient, powerful and easy to use. It provides C++ wrappers for the most popular packet processing engines such as libpcap, Npcap, WinPcap, DPDK, AF_XDP and PF_RING.

KitNET-py

KitNET is a lightweight online anomaly detection algorithm, which uses an ensemble of autoencoders.

Kitsune-py

A network intrusion detection system based on incremental statistics (AfterImage) and an ensemble of autoencoders (KitNET)

anomaly-detection-resources

Anomaly detection related books, papers, videos, and toolboxes

ddosflowgen

Simulate DDoS attacks and generate traffic datasets

Cyber-Security-Dataset-collections

Awesome Cyber-Security Data-sets Collection :stuck_out_tongue:

Network-Intrusion-Detection

Machine Learning with the NSL-KDD dataset for Network Intrusion Detection

Network-Intrusion-detection-with-machine-learning

awesome-ml-for-cybersecurity

:octocat: Machine Learning for Cyber Security

SDN-OpenNetMon

Accurate and precise OpenFlow Monitoring POX module