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Towards Interpretability over Smart Contract Vulnerability Detection based on Deep Neural Networks

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Explanation-Vulnerability-Detector

This repo is a python implementation of ...

Requirements

Required Packages

  • python3 or above
  • TensorFlow 2.0 or above
  • sklearn for model evaluation

Run the following script to install the required packages.

pip install --upgrade pip
pip install --upgrade tensorflow
pip install scikit-learn

Required Dataset

source code

Dataset structure in this project

Here, we present the dataset structure in our project.

${Explanation-Vulnerability-Detector}
├── 
│   ├── 
│   ├── 
│   └── 
└── 
    ├── 
    ├── 
    └── 

Note:

Running Project

Examples:

References

  1. Smart Contract Vulnerability Detection Using Graph Neural Networks. IJCAI 2020. GNNSCVulDetector.
@inproceedings{ijcai2020-454,
  title     = {Smart Contract Vulnerability Detection using Graph Neural Network},
  author    = {Zhuang, Yuan and Liu, Zhenguang and Qian, Peng and Liu, Qi and Wang, Xiang and He, Qinming},
  booktitle = {Proceedings of the Twenty-Ninth International Joint Conference on
               Artificial Intelligence, {IJCAI-20}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization}, 
  pages     = {3283--3290},
  year      = {2020},
}

  1. Combining Graph Neural Networks with Expert Knowledge for Smart Contract Vulnerability Detection. TKDE(Under Review). GPSCVulDetector.

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