R-SNN: An Analysis and Design Methodology for Robustifying Spiking Neural Networks against Adversarial Attacks through Noise Filters for Dynamic Vision Sensors

1 September 2021

Papers citing "R-SNN: An Analysis and Design Methodology for Robustifying Spiking Neural Networks against Adversarial Attacks through Noise Filters for Dynamic Vision Sensors"

6 / 6 papers shown

Title
Towards Effective and Sparse Adversarial Attack on Spiking Neural Networks via Breaking Invisible Surrogate Gradients Li Lun Kunyu Feng Qinglong Ni Ling Liang Yuan Wang Ying Li Dunshan Yu Xiaoxin Cui AAML 115 0 0 05 Mar 2025
A Homomorphic Encryption Framework for Privacy-Preserving Spiking Neural Networks F. Nikfam Raffaele Casaburi Alberto Marchisio Maurizio Martina Mohamed Bennai 71 3 0 10 Aug 2023
Security-Aware Approximate Spiking Neural Networks Syed Tihaam Ahmad Ayesha Siddique K. A. Hoque AAML 51 3 0 12 Jan 2023
LaneSNNs: Spiking Neural Networks for Lane Detection on the Loihi Neuromorphic Processor Alberto Viale Alberto Marchisio Maurizio Martina Guido Masera Mohamed Bennai 65 13 0 03 Aug 2022
Special Session: Towards an Agile Design Methodology for Efficient, Reliable, and Secure ML Systems Shail Dave Alberto Marchisio Muhammad Abdullah Hanif Amira Guesmi Aviral Shrivastava Ihsen Alouani Mohamed Bennai 75 14 0 18 Apr 2022
Towards Energy-Efficient and Secure Edge AI: A Cross-Layer Framework Mohamed Bennai Alberto Marchisio Rachmad Vidya Wicaksana Putra Muhammad Abdullah Hanif 98 34 0 20 Sep 2021