Encrypted Image Classification with Low Memory Footprint using Fully Homomorphic Encryption

ePrint Report: Encrypted Image Classification with Low Memory Footprint using Fully Homomorphic Encryption

Lorenzo Rovida, Alberto Leporati

Classifying images has become a straightforward and accessible task, thanks to the advent of Deep Neural Networks. Nevertheless, not much attention is given to the privacy concerns associated with sensitive data contained in images. In this study, we propose a solution to this issue by exploring an intersection between Machine Learning and cryptography.
In particular, Fully Homomorphic Encryption (FHE) emerges as a promising …

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