MohdSaif-1807/Network-Intrusion-Detection-System-Using-Machine-Learning-and-Deep-Learning

Cyber Security: Development of Network Intrusion Detection System (NIDS), with Machine Learning and Deep Learning (RNN) models, MERN web I/O System. The deployed project link is as follows.

22
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Experimental

This system helps organizations protect their networks by detecting cyberattacks and unusual network activity. You input potential 'hacking parameters' through a web interface, and it analyzes this data to identify and classify different types of network intrusions. It's designed for cybersecurity analysts, network administrators, or IT security personnel who need to monitor and respond to network threats.

No commits in the last 6 months.

Use this if you need a web-based tool to analyze specific network traffic parameters and determine if they indicate a cyberattack, receiving alerts and information about the threat type.

Not ideal if you need a passively deployed, real-time intrusion prevention system that automatically blocks threats without manual input, or if you require analysis of full network packet captures.

network-security cybersecurity-analysis threat-detection IT-security anomaly-detection
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 6 / 25
Maturity 8 / 25
Community 8 / 25

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Stars

21

Forks

2

Language

EJS

License

Last pushed

Apr 29, 2024

Commits (30d)

0

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