Sneaky Spikes: Uncovering Stealthy Backdoor Attacks in Spiking Neural Networks with Neuromorphic Data
May 17, 2024 · View on GitHub
Corresponding code for the paper: "Sneaky Spikes: Uncovering Stealthy Backdoor Attacks in Spiking Neural Networks with Neuromorphic Data", at Network and Distributed System Security (NDSS) 2024.
A guide to the code is available here.
Examples
Static Triggers




Moving Triggers



Smart Triggers
Clean Image

Trigger in the least important area

Trigger in the most important area

Dynamic Triggers
Attack Overview

Dynamic Examples
| γ | 0.1 | 0.05 | 0.01 |
|---|---|---|---|
| Clean image | ![]() | ![]() | ![]() |
| Noise | ![]() | ![]() | ![]() |
| Projected Noise | ![]() | ![]() | ![]() |
| Backdoor image | ![]() | ![]() | ![]() |
Authors
Gorka Abad, Oguzhan Ersoy, Stjepan Picek, and Aitor Urbieta.
How to cite
@inproceedings{abad2024sneaky,
title={Sneaky Spikes: Uncovering Stealthy Backdoor Attacks in Spiking Neural Networks with Neuromorphic Data.},
author={Abad, Gorka and Ersoy, Oguzhan and Picek, Stjepan and Urbieta, Aitor.},
booktitle={NDSS},
year={2024}
}
License
This project is licensed under the MIT License - see the LICENSE file for details.











