Full Stack Network Intrusion Detection System Using Machine Learning

Full Stack Network Intrusion Detection System Using Machine Learning

Youtube video: https://youtu.be/2MVfZPuhJaE?si=xco3rynjCk3h6R0y

Abstract :

Network intrusions pose a significant threat to organizational networks, resulting in substantial financial losses and reputational damage. This project proposes a full-stack network intrusion detection system using machine learning techniques. The system collects and analyzes network traffic data, extracts relevant features, and trains machine learning models to detect intrusions. The project implements a web-based interface for system administrators to monitor and manage the system. Experimental results demonstrate the effectiveness of the proposed system in detecting network intrusions with high accuracy. The project contributes to the development of robust network intrusion detection systems using machine learning techniques.

Keywords: Network Intrusion Detection Machine Learning Full Stack Development Cybersecurity Network Security Intrusion Detection System Machine Learning Algorithms Web Development Data Analysis Data Visualization

Project include:

1. Synopsis

2. PPT

3. Research Paper

4. Code

5. Explanation video

6. Documents

7. Report

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