MATLAB Source Code Implementation for Intrusion Detection

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Resource Overview

MATLAB source files implementing network data intrusion detection using the libSVM toolbox for feature classification. Includes data normalization, parameter optimization via cross-validation, SVM model construction, and performance evaluation. The package contains detailed documentation with code implementation explanations.

Detailed Documentation

This project implements network intrusion detection using MATLAB source files. We utilize the libSVM toolbox for feature classification, with key implementation steps including: data normalization using z-score or min-max scaling methods, parameter optimization through k-fold cross-validation grid search, SVM model training with RBF kernel selection, and performance evaluation using metrics like accuracy, precision, and recall. The algorithm employs feature scaling to ensure equal contribution of all input dimensions, while cross-validation systematically determines optimal C and gamma parameters. The compressed package includes comprehensive documentation detailing function usage, algorithm workflow, and example code execution sequences to facilitate understanding.

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