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Spiking Neural Networks Are Harder to Steal: A Benchmark Study of Model Stealing Attacks
Machine learning models deployed behind query interfaces expose more than their predictions, because an adversary can use those predictions to rebuild the model itself. Model stealing attacks (MSAs) exploit this exposure by training a surrogate model that replicates the decision behavior of a target
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