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README.md

Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

This repository provides source codes of our methodology for generating robust SNNs, and to compare with CNNs. For more details, please follow our paper. If you used these results in your research, please refer to the paper:

EL-ALLAMI Rida, MARCHISIO Alberto, SHAFIQUE Muhammad and ALOUANI Ihsen. Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters. In: IEEE/ACM 24th Conference on Design, Automation and Test in Europe (DATE '21). Virtual Event, 2021.
@inproceedings{elallami2020securing,
      title={Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters}, 
      author={Rida El-Allami and Alberto Marchisio and Muhammad Shafique and Ihsen Alouani},
      year={2021},
      booktitle={Proceedings of the 24th Conference on Design, Automation and Test in Europe},
      series = {DATE '21}
}

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Securing Deep Spiking Neural Networks against Adversarial Attacks through Inherent Structural Parameters

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