This repository contains the code and data associated with our CCS'23 publication (camera-ready version coming soon). An extended version of the paper, including an appendix, can be found on arXiv.
If you find this research helpful for your publications, please kindly cite:
@inproceedings{he2023finer,
title={FINER: Enhancing State-of-the-art Classifiers with Feature Attribution to Facilitate Security Analysis},
author={He, Yiling and Lou, Jian and Qin, Zhan and Ren, Kui},
booktitle={Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security},
pages={416--430},
year={2023}
}
conda env create --name FINER --file finer.yml
conda activate FINER
All scripts can be found in test/
. To run the experiments, use
python -m unittest test/test_damd.py
python -m unittest test/test_deepreflect.py
python -m unittest test/test_vuldeepecker.py