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--- |
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configs: |
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- config_name: default |
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data_files: |
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- split: train |
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path: "data/*.parquet" |
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--- |
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<h1 align="center"> HiGraph: A Large-Scale Hierarchical Graph Dataset </h1> |
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<div align="center"> |
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<img src="https://raw.githubusercontent.com/hzcheney/HiGraph/refs/heads/master/assets/h_logo.svg" width="100" height="100"> |
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<p><strong>Hierarchical Graph Dataset for Malware Analysis with Function Call Graphs and Control Flow Graphs</strong></p> |
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<img src="https://img.shields.io/badge/🤗%20Hugging%20Face-Datasets-yellow" alt="Hugging Face" /> |
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<img src="https://img.shields.io/badge/Dataset-6.17GB-blue" alt="Dataset Size" /> |
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<img src="https://img.shields.io/badge/Samples-595K%20FCGs-green" alt="Function Call Graphs" /> |
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<img src="https://img.shields.io/badge/CFGs-200M%2B-brightgreen" alt="Control Flow Graphs" /> |
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<img src="https://img.shields.io/badge/Period-2012--2022-orange" alt="Time Period" /> |
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<img src="https://img.shields.io/badge/License-CC--BY--NC--SA-red" alt="License" /> |
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A comprehensive hierarchical graph-based dataset for malware analysis and detection. |
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[Overview](#overview) • [Dataset Statistics](#dataset-statistics) • [Interactive Explorer](#interactive-visualization) • [Download](#download-dataset) |
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</div> |
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## Overview |
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**HiGraph** is a novel, large-scale dataset that models each application as a hierarchical graph: a local **Control Flow Graph (CFG)** capturing intra-function logic and a global **Function Call Graph (FCG)** capturing inter-function interactions. |
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Graph-based methods have shown great promise in malware analysis, yet the lack of large-scale, hierarchical graph datasets limits further advances in this field. This hierarchical design facilitates the development of robust detection models that are more resilient to obfuscation, model aging, and malware evolution. |
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<div align="center"> |
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</div> |
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### Key Features |
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- 🔍 **Hierarchical Graph Structure**: Two-level representation with FCGs and CFGs |
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- 📈 **Large Scale**: 200M+ Control Flow Graphs and 595K+ Function Call Graphs |
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- 🏷️ **Rich Semantic Information**: Preserves crucial structural details for malware analysis |
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- 📊 **Comprehensive Coverage**: 11-year temporal span (2012-2022) |
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- 🎯 **Benchmark Ready**: Designed for advancing hierarchical graph learning in cybersecurity |
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## Dataset Statistics |
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<div align="center"> |
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| Class | Time Period | # Apps | **Function Call Graph** || **Control Flow Graph** ||| |
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|-------|-------------|--------|---------------------|--|--------------------|--|--| |
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| | | | **Avg # Nodes** | **Avg # Edges** | **# Graphs** | **Avg # Nodes** | **Avg # Edges** | |
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| **Malicious** | 2012.01-2022.12 | 57,184 | 266.48 | 491.67 | 6,925,406 | 12.29 | 14.94 | |
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| **Benign** | 2012.01-2022.12 | 538,027 | 791.54 | 1,414.51 | 194,866,679 | 12.17 | 13.94 | |
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</div> |
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## Interactive Visualization |
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Explore the hierarchical structure of malware samples through our interactive visualization tool: |
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<div align="center"> |
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🔗 **[Launch Interactive Explorer](https://higraph.org/)** |
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*Click to explore the complete dataset structure and sample graphs* |
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*Sample Function Call Graph (FCG) visualization* |
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</div> |
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## Download Dataset |
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Access the complete HiGraph dataset through multiple platforms: |
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<div align="center"> |
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| Platform | Description | Link | |
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|----------|-------------|------| |
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| 🤗 **Hugging Face** | Primary dataset repository | [View on Hugging Face](https://huggingface.co/datasets/hzcheney/Hi-Graph/tree/main) | |
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| 🌐 **Project Page** | Interactive explorer | [HiGraph Explorer](https://higraph.org/) | |
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</div> |
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## Requirements |
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- Python >= 3.9 |
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- torch==2.6.0 |
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- torch-geometric==2.6.1 |
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Install dependencies: |
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```bash |
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pip install -r requirements.txt |
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``` |
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## 📄 License |
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This dataset is licensed under the **Creative Commons Attribution-NonCommercial-ShareAlike (CC-BY-NC-SA)** license. See the [LICENSE](LICENSE) file for details. |