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TinyML-based Intrusion Detection for Electric Vehicle Charging Infrastructure (EVCI), utilizing feature selection and hybrid pruning for efficient real-time cybersecurity.

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Western-OC2-Lab/TinyML-NetworkSecurity-EVCI

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TinyML-NetworkSecurity-EVCI

This repository contains the complete workflow for TinyML-based network security for Electric Vehicle Charging Infrastructure (EVCI).

Repository Structure

0_Dataset Creation

This folder contains the final dataset files used for model training and evaluation:

  • Final_EVSE_A.csv
  • Final_EVSE_B.csv

1_ModelTrainingHyperparameterOptimization

Contains scripts and logs related to model training and hyperparameter tuning.

2_Feature Selection

Includes scripts and results for selecting the most relevant features for each model.

3_Prunings

Stores model pruning experiments to optimize efficiency.

4_Results

All final results, including performance metrics, evaluation reports, and visualizations, are saved in this directory.

RaspberryPi

This folder contains all files required to deploy and evaluate the trained TinyML models on a Raspberry Pi device.

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TinyML-based Intrusion Detection for Electric Vehicle Charging Infrastructure (EVCI), utilizing feature selection and hybrid pruning for efficient real-time cybersecurity.

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