In our publication, "Smarter Evolution: Enhancing Evolutionary Black-Box Fuzzing with Adaptive Models", we presented an approach to bridge the gap between existing gray box fuzzing strategies and the real-world black box setting of fuzzing industrial control systems. This Jupyter Notebook was used to analyze the data created by the various fuzzing runs and to generate the corresponding figures. It requires the data that we generated during our experiments which can be downloaded here.
Feel free to use this Notebook and adapt it to your needs.
The file models.md contains details on how we defined the models that we used for our evaluation.
If you use our work in a publication, we would appreciate it if you would cite our work as follows:
@article{borcherding2023smarter,
author = {Anne Borcherding and Martin Morawetz and Steffen Pfrang},
title = {Smarter Evolution: Enhancing Evolutionary Black-Box Fuzzing with Adaptive Models},
year = 2023,
journal = {Sensors},
doi = {https://doi.org/10.3390/s23187864},
url = {https://www.mdpi.com/1424-8220/23/18/7864}
}