# sifat192/hybrid-network-intrusion-detection-ml-qml architecture

> Architecture diagram of the GitHub repository sifat192/hybrid-network-intrusion-detection-ml-qml, generated by GitDiagram from its file tree, README and a sample of source files (last updated 2026-09-28). It is an AI-made overview: check details against the source.

- Interactive diagram: https://gitdiagram.com/sifat192/hybrid-network-intrusion-detection-ml-qml
- Repository: https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml

## Overview

This repository is a notebook-based network intrusion detection study comparing classical machine learning with a Qiskit quantum classifier. Its documented workflow integrates traffic datasets, prepares and analyzes features, trains models, and compares evaluation results. The README supports the workflow and capabilities shown here; the notebook is the only listed implementation file, and its cells were not provided for inspection, so internal call relationships cannot be verified.

Main entry points: [`Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb) (Feature scaling)

## Diagram (Mermaid)

```mermaid
flowchart TD

subgraph group_data["Data preparation"]
  node_integration["Data integration"]
  node_eda["Exploratory analysis"]
  node_preprocessing["Cleaning and preprocessing"]
  node_engineering["Feature engineering"]
  node_scaling["Feature scaling"]
end

subgraph group_classical["Classical learning"]
  node_classifiers["Classical classifiers"]
  node_feature_selection["Feature selection"]
  node_pca["PCA reduction"]
end

subgraph group_quantum["Quantum learning"]
  node_feature_map["Quantum feature map"]
  node_quantum_kernel["Fidelity quantum kernel"]
  node_qsvc["Quantum QSVC"]
end

subgraph group_evaluation["Evaluation"]
  node_evaluation["Performance comparison"]
  node_results["Classification metrics"]
end

node_traffic_sources["Traffic CSVs"]

node_traffic_sources -->|"integrate"| node_integration
node_integration -->|"analyze"| node_eda
node_eda -->|"inform cleaning"| node_preprocessing
node_preprocessing -->|"prepare features"| node_engineering
node_engineering -->|"scale features"| node_scaling
node_scaling -->|"train models"| node_classifiers
node_scaling -->|"select features"| node_feature_selection
node_scaling -->|"reduce dimensions"| node_pca
node_feature_selection -->|"encode features"| node_feature_map
node_pca -->|"encode features"| node_feature_map
node_feature_map -->|"compute kernel"| node_quantum_kernel
node_quantum_kernel -->|"fit classifier"| node_qsvc
node_classifiers -->|"evaluate"| node_evaluation
node_qsvc -->|"evaluate"| node_evaluation
node_evaluation -->|"report metrics"| node_results

click node_integration "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_eda "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_preprocessing "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_engineering "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_scaling "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_classifiers "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_feature_selection "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_pca "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_feature_map "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_quantum_kernel "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_qsvc "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_evaluation "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"
click node_results "https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb"

classDef toneNeutral fill:#f8fafc,stroke:#334155,stroke-width:1.5px,color:#0f172a
classDef toneBlue fill:#dbeafe,stroke:#2563eb,stroke-width:1.5px,color:#172554
classDef toneAmber fill:#fef3c7,stroke:#d97706,stroke-width:1.5px,color:#78350f
classDef toneMint fill:#dcfce7,stroke:#16a34a,stroke-width:1.5px,color:#14532d
classDef toneRose fill:#ffe4e6,stroke:#e11d48,stroke-width:1.5px,color:#881337
classDef toneIndigo fill:#e0e7ff,stroke:#4f46e5,stroke-width:1.5px,color:#312e81
classDef toneTeal fill:#ccfbf1,stroke:#0f766e,stroke-width:1.5px,color:#134e4a
class node_integration,node_eda,node_preprocessing,node_engineering,node_scaling toneBlue
class node_classifiers,node_feature_selection,node_pca toneAmber
class node_feature_map,node_quantum_kernel,node_qsvc toneMint
class node_evaluation,node_results toneRose
class node_traffic_sources toneIndigo
```

## Components

### Data preparation

- [Data integration](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`
- [Exploratory analysis](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`
- [Cleaning and preprocessing](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`
- [Feature engineering](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`
- [Feature scaling](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`

### Classical learning

- [Classical classifiers](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`
- [Feature selection](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`
- [PCA reduction](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`

### Quantum learning

- [Quantum feature map](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`
- [Fidelity quantum kernel](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`
- [Quantum QSVC](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`

### Evaluation

- [Performance comparison](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`
- [Classification metrics](https://github.com/sifat192/hybrid-network-intrusion-detection-ml-qml/blob/main/Hybrid_Network_Intrusion_Detection_ML_QML.ipynb): `Hybrid_Network_Intrusion_Detection_ML_QML.ipynb`

### Other components

- **Traffic CSVs**

## Connections

- Traffic CSVs → Data integration: integrate
- Data integration → Exploratory analysis: analyze
- Exploratory analysis → Cleaning and preprocessing: inform cleaning
- Cleaning and preprocessing → Feature engineering: prepare features
- Feature engineering → Feature scaling: scale features
- Feature scaling → Classical classifiers: train models
- Feature scaling → Feature selection: select features
- Feature scaling → PCA reduction: reduce dimensions
- Feature selection → Quantum feature map: encode features
- PCA reduction → Quantum feature map: encode features
- Quantum feature map → Fidelity quantum kernel: compute kernel
- Fidelity quantum kernel → Quantum QSVC: fit classifier
- Classical classifiers → Performance comparison: evaluate
- Quantum QSVC → Performance comparison: evaluate
- Performance comparison → Classification metrics: report metrics