Event Burst Trigger: An Availability Backdoor Attack on Event-Based SNN Object Detection

arXiv:2607.09115 · cs.CV, cs.CR · Submitted 2026-07-10 · Read on arXiv

cs.CV, cs.CR

Submitted: 2026-07-10

Updated: 2026-07-13

Comments: The 56th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN 2026)

Code: https://github.com/ultralytics/ultralytics

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Accuracy — 21× in this paper · explained in 1 episode
• Edge AI — 6× in this paper · explained in 2 episodes
• Non-Maximum Suppression — 6× in this paper
• Robustness — 4× in this paper · explained in 5 episodes
• AUC — 3× in this paper · explained in 2 episodes
• Core — 3× in this paper · explained in 2 episodes
• Event Burst Trigger — 3× in this paper
• Spiking Neural Networks (SNNs) — 3× in this paper · explained in 3 episodes
• Alignment — 2× in this paper · explained in 1 episode
• Annual Design Automation Conference — 2× in this paper
• Edge Deployment — 2× in this paper · explained in 2 episodes
• Edge Devices — 2× in this paper · explained in 2 episodes
• International Conference on Computer Vision — 2× in this paper
• Loss Function — 2× in this paper · explained in 2 episodes
• Sparsity — 2× in this paper · explained in 4 episodes
• AVERAGE SPIKE FIRING RATE — 1× in this paper
• Ablation — 1× in this paper · explained in 1 episode
• Ablation study — 1× in this paper · explained in 1 episode
• Adversarial Attacks — 1× in this paper · explained in 1 episode
• Adversarial Examples — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Communication Overhead — 1× in this paper · explained in 2 episodes
• Conference on Computer Vision and Pattern Recognition — 1× in this paper
• Consistency — 1× in this paper · explained in 3 episodes
• Energy Efficiency — 1× in this paper · explained in 3 episodes
• Model Merging — 1× in this paper · explained in 2 episodes
• Resource Constraints — 1× in this paper · explained in 3 episodes

Sources

• Integer-Valued Training and Spike-Driven Inference Spiking Neural Network for High-performance and Energy-efficient Object Detection
• Sponge Examples: Energy-Latency Attacks on Neural Networks
• BadNets: Identifying Vulnerabilities in the Machine Learning Model Supply Chain
• A Large Scale Event-based Detection Dataset for Automotive

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