On the Relationship between Model Quantization and Model Inversion Attacks

Reported by arXiv cs.CR (Rongke Liu, Youwen Zhu)

Summary by Cyber Security News2 Oct 2026, 06:00 CET

About this summary. This is a short excerpt from the description that arXiv cs.CR published with its article. Cyber Security News did not report or verify the underlying story. Read the original: https://arxiv.org/abs/2610.00382

arXiv:2610.00382v1 Announce Type: new Abstract: Model quantization reduces the numerical precision of neural network weights and activations to lower storage and computational costs. Model inversion attacks recover or reconstruct sensitive training data or inference inputs from model outputs or intermediate features, so quantization may also alter their effectiveness. However, two questions remain unresolved: How does model quantization affect model inversion?

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