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

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.

A thesis submitted for the degree of Master of Science in Computer Networks and Security

An Intrusion Detection System based on Deep Belief Networks

CICIDS2017 dataset

Data stream analytics: Implement online learning methods to address concept drift and model drift in dynamic data streams. Code for the paper entitled "A Multi-Stage Automated Online Network Data Stream Analytics Framework for IIoT Systems" published in IEEE Transactions on Industrial Informatics.

Attack Detection, Parameter Optimization and Performance Analysis in Enterprise Networks (ML Networks) for Intrusion Detection System IDS.

This repository contains my third year dissertation. My dissertation focused in evaluating and creating a DNN for a Network Intrusion Detection System (NIDS).

An Advanced IDS with HoneyPot Fusion for Proactive Threat Mitigation and Detection; Research Project