Time Is All It Takes: Spike-Retiming Attacks on Event-Driven Spiking Neural Networks
Fuente:
arXiv
Saved in:
| Main Authors: | Yu, Yi, Zhang, Qixin, Ye, Shuhan, Lin, Xun, Wei, Qianshan, Wang, Kun, Yang, Wenhan, Tao, Dacheng, Jiang, Xudong |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Spike-PTSD: A Bio-Plausible Adversarial Example Attack on Spiking Neural Networks via PTSD-Inspired Spike Scaling
by: Jin, Lingxin, et al.
Published: (2026)
by: Jin, Lingxin, et al.
Published: (2026)
BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron
by: Miah, Abdullah Arafat, et al.
Published: (2026)
by: Miah, Abdullah Arafat, et al.
Published: (2026)
Input-Specific and Universal Adversarial Attack Generation for Spiking Neural Networks in the Spiking Domain
by: Raptis, Spyridon, et al.
Published: (2025)
by: Raptis, Spyridon, et al.
Published: (2025)
Data Poisoning-based Backdoor Attack Framework against Supervised Learning Rules of Spiking Neural Networks
by: Jin, Lingxin, et al.
Published: (2024)
by: Jin, Lingxin, et al.
Published: (2024)
Unsupervised Backdoor Detection and Mitigation for Spiking Neural Networks
by: Li, Jiachen, et al.
Published: (2025)
by: Li, Jiachen, et al.
Published: (2025)
Sneaky Spikes: Uncovering Stealthy Backdoor Attacks in Spiking Neural Networks with Neuromorphic Data
by: Abad, Gorka, et al.
Published: (2023)
by: Abad, Gorka, et al.
Published: (2023)
Do Spikes Protect Privacy? Investigating Black-Box Model Inversion Attacks in Spiking Neural Networks
by: Poursiami, Hamed, et al.
Published: (2025)
by: Poursiami, Hamed, et al.
Published: (2025)
Membership Privacy Evaluation in Deep Spiking Neural Networks
by: Li, Jiaxin, et al.
Published: (2024)
by: Li, Jiaxin, et al.
Published: (2024)
SNNGX: Securing Spiking Neural Networks with Genetic XOR Encryption on RRAM-based Neuromorphic Accelerator
by: Wong, Kwunhang, et al.
Published: (2024)
by: Wong, Kwunhang, et al.
Published: (2024)
Attacking the Spike: On the Transferability and Security of Spiking Neural Networks to Adversarial Examples
by: Xu, Nuo, et al.
Published: (2022)
by: Xu, Nuo, et al.
Published: (2022)
Privacy-Preserving Spiking Neural Networks: A Deep Dive into Encryption Parameter Optimisation
by: Pulivathi, Mahitha, et al.
Published: (2025)
by: Pulivathi, Mahitha, et al.
Published: (2025)
Transferable Adversarial Attacks on SAM and Its Downstream Models
by: Xia, Song, et al.
Published: (2024)
by: Xia, Song, et al.
Published: (2024)
Efficient Encrypted Computation in Convolutional Spiking Neural Networks with TFHE
by: Guo, Longfei, et al.
Published: (2026)
by: Guo, Longfei, et al.
Published: (2026)
On the Adversarial Robustness of Spiking Neural Networks Trained by Local Learning
by: Lin, Jiaqi, et al.
Published: (2025)
by: Lin, Jiaqi, et al.
Published: (2025)
Convergent Differential Privacy Analysis for General Federated Learning
by: Sun, Yan, et al.
Published: (2024)
by: Sun, Yan, et al.
Published: (2024)
PrivSpike: Employing Homomorphic Encryption for Private Inference of Deep Spiking Neural Networks
by: Njungle, Nges Brian, et al.
Published: (2025)
by: Njungle, Nges Brian, et al.
Published: (2025)
Sparse by Rule: Probability-Based N:M Pruning for Spiking Neural Networks
by: Ye, Shuhan, et al.
Published: (2025)
by: Ye, Shuhan, et al.
Published: (2025)
A Homomorphic Encryption Framework for Privacy-Preserving Spiking Neural Networks
by: Nikfam, Farzad, et al.
Published: (2023)
by: Nikfam, Farzad, et al.
Published: (2023)
Time-Distributed Backdoor Attacks on Federated Spiking Learning
by: Abad, Gorka, et al.
Published: (2024)
by: Abad, Gorka, et al.
Published: (2024)
Adversarially Robust Spiking Neural Networks with Sparse Connectivity
by: Schmolli, Mathias, et al.
Published: (2025)
by: Schmolli, Mathias, et al.
Published: (2025)
The Robustness of Spiking Neural Networks in Federated Learning with Compression Against Non-omniscient Byzantine Attacks
by: Nguyen, Manh V., et al.
Published: (2025)
by: Nguyen, Manh V., et al.
Published: (2025)
Large Language Models Merging for Enhancing the Link Stealing Attack on Graph Neural Networks
by: Guan, Faqian, et al.
Published: (2024)
by: Guan, Faqian, et al.
Published: (2024)
Temporal-Guided Spiking Neural Networks for Event-Based Human Action Recognition
by: Yang, Siyuan, et al.
Published: (2025)
by: Yang, Siyuan, et al.
Published: (2025)
Learning from Dense Events: Towards Fast Spiking Neural Networks Training via Event Dataset Distillation
by: Ye, Shuhan, et al.
Published: (2025)
by: Ye, Shuhan, et al.
Published: (2025)
CtrlAttack: A Unified Attack on World-Model Control in Diffusion Models
by: Xu, Shuhan, et al.
Published: (2026)
by: Xu, Shuhan, et al.
Published: (2026)
Watermarking Neuromorphic Brains: Intellectual Property Protection in Spiking Neural Networks
by: Poursiami, Hamed, et al.
Published: (2024)
by: Poursiami, Hamed, et al.
Published: (2024)
Spikewhisper: Temporal Spike Backdoor Attacks on Federated Neuromorphic Learning over Low-power Devices
by: Fu, Hanqing, et al.
Published: (2024)
by: Fu, Hanqing, et al.
Published: (2024)
Defending Against Neural Network Model Inversion Attacks via Data Poisoning
by: Zhou, Shuai, et al.
Published: (2024)
by: Zhou, Shuai, et al.
Published: (2024)
Backdoor Attacks against Hybrid Classical-Quantum Neural Networks
by: Guo, Ji, et al.
Published: (2024)
by: Guo, Ji, et al.
Published: (2024)
ME: Trigger Element Combination Backdoor Attack on Copyright Infringement
by: Yang, Feiyu, et al.
Published: (2025)
by: Yang, Feiyu, et al.
Published: (2025)
Backdoor Attacks against No-Reference Image Quality Assessment Models via a Scalable Trigger
by: Yu, Yi, et al.
Published: (2024)
by: Yu, Yi, et al.
Published: (2024)
Hijacking Attacks against Neural Networks by Analyzing Training Data
by: Ge, Yunjie, et al.
Published: (2024)
by: Ge, Yunjie, et al.
Published: (2024)
Revisiting Edge Perturbation for Graph Neural Network in Graph Data Augmentation and Attack
by: Liu, Xin, et al.
Published: (2024)
by: Liu, Xin, et al.
Published: (2024)
Towards Detecting IoT Event Spoofing Attacks Using Time-Series Classification
by: Maroof, Uzma, et al.
Published: (2024)
by: Maroof, Uzma, et al.
Published: (2024)
When Bots Take the Bait: Exposing and Mitigating the Emerging Social Engineering Attack in Web Automation Agent
by: Wu, Xinyi, et al.
Published: (2026)
by: Wu, Xinyi, et al.
Published: (2026)
External Data Extraction Attacks against Retrieval-Augmented Large Language Models
by: He, Yu, et al.
Published: (2025)
by: He, Yu, et al.
Published: (2025)
Network Attack Traffic Detection With Hybrid Quantum-Enhanced Convolution Neural Network
by: Wang, Zihao, et al.
Published: (2025)
by: Wang, Zihao, et al.
Published: (2025)
A Practical Trigger-Free Backdoor Attack on Neural Networks
by: Wang, Jiahao, et al.
Published: (2024)
by: Wang, Jiahao, et al.
Published: (2024)
A Survey of Safety on Large Vision-Language Models: Attacks, Defenses and Evaluations
by: Ye, Mang, et al.
Published: (2025)
by: Ye, Mang, et al.
Published: (2025)
ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks
by: Ren, Zhiyao, et al.
Published: (2025)
by: Ren, Zhiyao, et al.
Published: (2025)
Similar Items
-
Spike-PTSD: A Bio-Plausible Adversarial Example Attack on Spiking Neural Networks via PTSD-Inspired Spike Scaling
by: Jin, Lingxin, et al.
Published: (2026) -
BadSNN: Backdoor Attacks on Spiking Neural Networks via Adversarial Spiking Neuron
by: Miah, Abdullah Arafat, et al.
Published: (2026) -
Input-Specific and Universal Adversarial Attack Generation for Spiking Neural Networks in the Spiking Domain
by: Raptis, Spyridon, et al.
Published: (2025) -
Data Poisoning-based Backdoor Attack Framework against Supervised Learning Rules of Spiking Neural Networks
by: Jin, Lingxin, et al.
Published: (2024) -
Unsupervised Backdoor Detection and Mitigation for Spiking Neural Networks
by: Li, Jiachen, et al.
Published: (2025)