This repo will contain all the code base for the machine learning (ML) experimentation of network-based Intrusion Detection System (NIDS).

A deep learning-based network intrusion detection system using 1D CNNs trained on CICIDS2017 to classify network traffic as benign or malicious.

My team is currently build a nids any suggestions or contributions are welcome.

TEAM 369 CYBER NID INFO WEBSITE

The project is done under the guidance of NID team and it was a part of intel perceptual computing competition.

This project implements a flow-based Network Intrusion Detection System (NIDS) designed from a Blue Team / SOC perspective. The system analyzes network traffic flows extracted from PCAP data and applies machine learning techniques to distinguish between benign and malicious activity.

A Network Intrusion Detection System (NIDS) monitors network traffic for suspicious activity and potential threats. It analyzes data packets for known attack patterns and anomalies, generating alerts for security teams. Tools like Snort and Suricata enhance network security and visibility without affecting normal operations.

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