Author

Ayana Moshruba

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Preprint Oct 2026

Characterizing Privacy Leakage in Spiking Neural Networks: A Systematic Analysis of Temporal Dynamics, Stochasticity, Neuronal Dynamics and Learning Mechanisms

Spiking neural networks (SNNs) encode information not only in whether neurons fire but also in when they fire, and this temporal dimension shapes what a trained network reveals about its training data. Biologically inspired firing patterns can reduce membership leakage in SNNs without changing the network architecture,...

Ayana Moshruba, Maryam Parsa · 0 citations

#artificial intelligence Preprint Oct 2026

Spiking Neural Networks Are Harder to Steal: A Benchmark Study of Model Stealing Attacks

These findings extend the known resilience of SNNs beyond attacks on training data to the replication of model functionality, strengthening the case for neuromorphic architectures in security-sensitive applications.

Ayana Moshruba, Maryam Parsa · 0 citations