LATIDIA · Ciberseguridad

T-Backdoor: Explotación de la redundancia temporal en datos neuromórficos para ataques de puerta trasera que conservan los picos en SNN

arXiv: 2609.30119v1Tipo de anuncio: nuevo Resumen: Los ataques de puerta trasera son una grave amenaza de seguridad para las redes neuronales profundas (DNN) y siguen siendo en gran medida poco explorados para las redes neuronales de picos (SNN). Ataques existentes primaril

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arXiv:2609.30119v1 Announce Type: new Abstract: Backdoor attacks are a serious security threat to deep neural networks (DNNs) and remain largely underexplored for spiking neural networks (SNNs). Existing attacks primarily introduce spatiotemporal triggers that induce deviations in the spike distribution of poisoned samples relative to their clean counterparts. To address this limitation, this work proposes a novel backdoor attack on SNNs, termed \textbf{T-Backdoor}, which operates using purely temporal triggers such as \textit{Rate}, \textit{Latency}, and \textit{Jitter} without introducing any spatial perturbation, making the shift in spike distributions significantly harder to detect. Through extensive experiments on three benchmark neuromorphic datasets: N-MNIST, CIFAR10-DVS, and N-Caltech101, and evaluation against seven baseline backdoor defense methods, we