Daemon to ban hosts that cause multiple authentication errors

Malicious traffic detection system

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Network Intrusion Detection KDDCup '99', NSL-KDD and UNSW-NB15

Monitor Network Traffic Per Executable, Beautifully Visualized

Wazuh - Ruleset

idstools: Snort and Suricata Rule and Event Utilities in Python (Including a Rule Update Tool)

Machine Learning for Computer Security

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

An All-In-One home intrusion detection system (IDS) solution for the Raspberry PI.

[ICMLC 2018] A Neural Network Architecture Combining Gated Recurrent Unit (GRU) and Support Vector Machine (SVM) for Intrusion Detection

Machine learning algorithms applied on log analysis to detect intrusions and suspicious activities.

Deep learning based object tracking with line crossing and area intrusion detection

Network Intrusion Detection System using Deep Learning Techniques

Simple Implementation of Network Intrusion Detection System. KddCup'99 Data set is used for this project. kdd_cup_10_percent is used for training test. correct set is used for test. PCA is used for dimension reduction. SVM and KNN supervised algorithms are the classification algorithms of project. Accuracy : %83.5 For SVM , %80 For KNN

A completely automated anomaly detector Zeek network flows files (conn.log).

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

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

A HIDS (host-based intrusion detection system) for verifying the integrity of a system.