Suricata is a network Intrusion Detection System, Intrusion Prevention System and Network Security Monitoring engine developed by the OISF and the Suricata community.

Security Onion is a free and open platform for threat hunting, enterprise security monitoring, and log management. It includes our own interfaces for alerting, dashboards, hunting, PCAP, detections, and case management. It also includes other tools such as osquery, CyberChef, Elasticsearch, Logstash, Kibana, Suricata, and Zeek.

Real-time HTTP Intrusion Detection

AD Security Intrusion Detection System

Slips, a free software behavioral Python intrusion prevention system (IDS/IPS) that uses machine learning to detect malicious behaviors in the network traffic. Stratosphere Laboratory, AIC, FEL, CVUT in Prague.

Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning

Code for IDS-ML: intrusion detection system development using machine learning algorithms (Decision tree, random forest, extra trees, XGBoost, stacking, k-means, Bayesian optimization..)

The OWASP SecureTea Project provides a one-stop security solution for various devices (personal computers / servers / IoT devices)

UnSupervised and Semi-Supervise Anomaly Detection / IsolationForest / KernelPCA Detection / ADOA / etc.

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

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

Data stream analytics: Implement online learning methods to address concept drift and model drift in data streams using the River library. Code for the paper entitled "PWPAE: An Ensemble Framework for Concept Drift Adaptation in IoT Data Streams" published in IEEE GlobeCom 2021.

Entropy scanner for Linux to detect packed or encrypted binaries related to malware. Finds malicious files and Linux processes and gives output with cryptographic hashes.

A Novel Statistical Analysis and Autoencoder Driven Intelligent Intrusion Detection Approach

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

An Intrusion Detection System based on Deep Belief Networks

Sandfly Security Agentless Compromise and Intrusion Detection System For Linux

Machine learning based Intrusion detection system (IDS)

OPNSense's Suricata IDS/IPS Detection Rules Against NMAP Scans

An online learning method used to address concept drift and model drift. Code for the paper entitled "A Lightweight Concept Drift Detection and Adaptation Framework for IoT Data Streams" published in IEEE Internet of Things Magazine.