Network-based-Intrusion-Detection-System
sayanbanerjee992
The case study on a Network-based Intrusion Detection System is a Machine Learning-based Web application based on https://arxiv.org/pdf/1903.02460.pdf research paper. I have performed both binary and multi-class classification to predict the presence of any intrusion-based signal. If present, then which type of signal is present in the network. I have used various techniques like under sampling and over sampling because of the imbalances in the dataset, then train the model using Machine Learning techniques like Logistic Regression, Random Forest, XGBoost. Lastly built a web application and deploy it to AWS using AWS EC2 instance
Growth over time
2 data points · 2023-03-01 → 2025-06-01How do you feel about this project?
Ask AI about Network-based-Intrusion-Detection-System
Question copied to clipboardWhat is the sayanbanerjee992/Network-based-Intrusion-Detection-System GitHub project? Description: "The case study on a Network-based Intrusion Detection System is a Machine Learning-based Web application based on https://arxiv.org/pdf/1903.02460.pdf research paper. I have performed both binary and multi-class classification to predict the presence of any intrusion-based signal. If present, then which type of signal is present in the network. I have used various techniques like under sampling and over sampling because of the imbalances in the dataset, then train the model using Machine Learning techniques like Logistic Regression, Random Forest, XGBoost. Lastly built a web application and deploy it to AWS using AWS EC2 instance". Written in Jupyter Notebook. Explain what it does, its main use cases, key features, and who would benefit from using it.
Question is copied to clipboard — paste it after the AI opens.
How to clone Network-based-Intrusion-Detection-System
Clone via HTTPS
Clone via SSH
Download ZIP
Download master.zipFound an issue?
Report bugs or request features on the Network-based-Intrusion-Detection-System issue tracker:
Open GitHub Issues