Machine Learning Algorithms on NSL-KDD dataset
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Updated
May 30, 2019 - Jupyter Notebook
Machine Learning Algorithms on NSL-KDD dataset
This is a software application to detect network intrusion by monitoring a network or system for malicious activity and predicts whether it is Normal or Abnormal(attacked with intrusion classes like DOS/PROBE/R2L/U2R).
A comparison between Statistical, Machine Learning, PCA, SVD, and REF methods
Feature based analysis using ML classifiers on the NSL-KDD Dataset
AN Intrusion Detection System using LSTM deep learning model to detect anomalous network Integrated with SDN POX controller to analyze and threats in real time
Network Intrusion Detection System using Machine Learning and Deep Learning
Python-based tool designed to process network traffic packets and extract features compliant with the NSL-KDD dataset format.
Code for intrusion detection system based on "Intrusion Detection System Using Machine Learning Algorithms" tutorial on Geeksforgeeks and Intrusion Detection on NSL KDD Github repository.
This is a software application to detect network intrusion by monitoring a network or system for malicious activity and predicts whether it is Normal or Abnormal(attacked with intrusion classes like DOS/PROBE/R2L/U2R).
This is a software application to detect network intrusion by monitoring a network or system for malicious activity and predicts whether it is Normal or Abnormal(attacked with intrusion classes like DOS/PROBE/R2L/U2R).
Creación de un Sistema de detección de intrusiones utilizando BPSO y SVM
Creating an Intrusion Detection System
This project was an attempt to use ML techniques to identify and prevent DDOS attacks.
Network Intrusion Detection System
A Feed-Forward and Pattern Recognition ANN Model for Network Intrusion Detection
Anomaly-Based Intrusion Detection System using Machine Learning (SVM & Neural Networks) on NSL-KDD and UNB-IDS 2018 datasets with adversarial robustness evaluation.
An automated tool for real-time feature engineering on network traffic data, optimized for intrusion detection using the NSL-KDD dataset. This tool processes live network traffic, extracts relevant features, and prepares data for use in machine learning models.
Comparative Analysis of Deep Learning and Machine Learning Models for Network Intrusion Detection
A Network Intrusion Detection System built using Machine Learning and LSTM models on the NSL-KDD dataset with Google Colab support.
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