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CNN Model for Secure Low Overhead Logic Locking Assignment

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CoLA: Convolutional Neural Network Model for Secure Low Overhead Logic Locking Assignment

This repository contains resources related to the Convolutional Neural Network (CNN) model tailored to the task of logic locking assignment, with an emphasis on minimizing overhead.
Yeganeh Aghamohammadi & Amin Rezaei

Contents

  • dataset: data images needed to run the experiment
  • paper: published paper based on the source code
  • src: source code and labels

Note

To extend the dataset, data extension methods available in Keras is suggested.

Citation

Journal Article:

@ARTICLE{Journal-2024,
  author={Aghamohammadi, Yeganeh and Rezaei, Amin},
  title={Machine Learning-based Security Evaluation and Overhead Analysis of Logic Locking},
  journal={Journal of Hardware and Systems Security},
  year={2024},
  volume={8},
  number={},
  pages={25–43},
  doi={10.1007/s41635-024-00144-8}
}

Conference Article:

@INPROCEEDINGS{Conference-2023,
  author={Aghamohammadi, Yeganeh and Rezaei, Amin},
  title={CoLA: Convolutional Neural Network Model for Secure Low Overhead Logic Locking Assignment}, 
  booktitle={Proceedings of the Great Lakes Symposium on VLSI (GLSVLSI)}, 
  year={2023},
  volume={},
  number={},
  pages={339–344},
  doi={10.1145/3583781.3590219}
}

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