This projects take a simple Network Intrusion Detection System, make it running on the docker swarm containers. Hence taking the received packets from the client to the server in realtime. Then applying the ML Model on the packet traffic in order to detect the Intrusion. There are 4 attack-class which this model can alert to. Namely: 1> DOS attack 2>R2L(Remote to Local) 3>U2R (User to Root) 4> Probe Attack.

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".

leetcode

My C++ Code for LeetCode OJ

mitmf

Framework for Man-In-The-Middle attacks

ml-ids-api

REST API serving the ML-IDS classifier (https://github.com/cstub/ml-ids)

mysql

Docker Official Image packaging for MySQL Community Server

network-intrusion-detection

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

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.