Anomaly-detection-system

Anomaly-detection 1-INTRODUCTION: In this project we propose a solution for the cyber attacks on networks as a machine learning based Intrusion detection system(IDS) and it's splitted to two parts: 1.1- Capturing the network flows and Features extraction: In this part we use CICFlowMeter to capture the flow and extract the features (83 feature),and tweaked its ui for a simpler usage. 1.2- Prediction: In order to achieve the highest accuracy we splitted the task into two stages to respectively detect the anomaly then classify it to a list of attacks we trained our model on, we used CSE-CIC-IDS2018 database to assure that we have the latest possible data on current cyber attacks. 2-Requirements: ### 2.1-For the Prediction Model: requirements.txt contains the needed python libraries. The needed python verson should be python3.. ### 2.2-For CICFlowMeter: - Java jdk - check CICFlowMeter-master/README.md 3-Running the project 3.1-Start the model server 3.2-Start CICFlowMeter 3.2.1-For Linux 4.2.2-For Windows