Popular GitHub Repositories for Intrusion Detection

Machine Learning for Computer Security

Streaming Anomaly Detection Framework in Python (Outlier Detection for Streaming Data)

Network Intrusion Detection System using Deep Learning Techniques

Anomaly Detection on Time-Evolving Streams in Real-time. Detecting intrusions (DoS and DDoS attacks), frauds, fake rating anomalies.

Sketch-Based Anomaly Detection in Streaming Graphs

This tool parses log data and allows to define analysis pipelines for anomaly detection. It was designed to run the analysis with limited resources and lowest possible permissions to make it suitable for production server use.

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

This repository contains an in-depth analysis of the Intrusion Detection Evaluation Dataset (CIC-IDS2017) for Intrusion Detection, showcasing the implementation and comparison of different machine learning models for binary and multi-class classification tasks.

Detecting malicious URLs using an autoencoder neural network

Machine Learning Based - Intrusion Detection System

IoT Attack Detection with machine learning

Adversarial Machine Learning applications on network-based Intrusion Detection System (IDS).

Python implementation of the MIDAS algorithm.

Scripts to generate and analyze the AIT alert data set (AIT-ADS)

A proof-of-concept for an Anomaly-based Intrusion Detection System based on a neural network.

convGRU based autoencoder for unsupervised & spatial-temporal anomaly detection in computer network (PCAP) traffic.

This repository includes supervised and unsupervised machine learning methods which are used to detect anomalies on network datasets. Decision Tree, Random Forest, Gradient Boost Tree, Naive Bayes, and Logistic Regression were used for supervised learning. K-Means was used for unsupervised learning.

Training of a simple Neural Network model as an Intrusion Detection System for Cybersecurity defense using Federated Learning with the TensorFlow Federated framework.

AEIDS is a prototype of anomaly-based intrusion detection system which works by remembering the pattern of legitimate network traffic using Autoencoder.

Anomaly Detection Discriminative GAN (ADD-GAN)