From the 1 of 6 linked papers with an AI index.
10 papers
MeMark: Membrane-Space Watermarking for Spiking Neural Networks
Roberto Riaño, Gorka Abad, Stjepan Picek +1
Spiking Neural Networks (SNNs) are increasingly distributed as pretrained checkpoints and reused as backbones for new tasks. However, current SNN watermarks are mainly verified aga…
Temporal Poisoning: Clean-Label Backdoors via Event Redistribution in SNNs
Roberto Riaño, Gorka Abad, Stjepan Picek +1
The paper introduces a clean‑label backdoor attack for spiking neural networks that subtly reshapes the timing of events in target‑class training streams, achieving near‑perfect at…
Removing the Trigger, Not the Backdoor: Alternative Triggers and Latent Backdoors
Gorka Abad, Ermes Franch, Stefanos Koffas +1
Current backdoor defenses assume that neutralizing a known trigger removes the backdoor. We show this trigger-centric view is incomplete: \emph{alternative triggers}, patterns perc…
SoK: The Last Line of Defense: On Backdoor Defense Evaluation
Gorka Abad, Marina KrÄek, Stefanos Koffas +7
Backdoor attacks pose a significant threat to deep learning models by implanting hidden vulnerabilities that can be activated by malicious inputs. While numerous defenses have been…
Backdoor Attacks on Transformers for Tabular Data: An Empirical Study
Bart Pleiter, Behrad Tajalli, Stefanos Koffas +4
Deep Neural Networks (DNNs) have shown great promise in various domains. However, vulnerabilities associated with DNN training, such as backdoor attacks, are a significant concern.…
Flashy Backdoor: Real-world Environment Backdoor Attack on SNNs with DVS Cameras
Roberto Riaño, Gorka Abad, Stjepan Picek +1
While security vulnerabilities in traditional Deep Neural Networks (DNNs) have been extensively studied, the susceptibility of Spiking Neural Networks (SNNs) to adversarial attacks…