Enhancing Privacy in Face Analytics Using Fully Homomorphic Encryption

arXiv:2404.16255v1 Announce Type: cross
Abstract: Modern face recognition systems utilize deep neural networks to extract salient features from a face. These features denote embeddings in latent space and are often stored as templates in a face recognition system. These embeddings are susceptible to data leakage and, in some cases, can even be used to reconstruct the original face image. To prevent compromising identities, template protection schemes are commonly employed. However, these schemes may still not prevent the leakage of soft …

abstract analytics arxiv cases cs.cr cs.cv data data leakage embeddings encryption extract face face recognition features homomorphic encryption modern networks neural networks privacy recognition space systems type