Privacy Preserving Face Retrieval in the Cloud for Mobile Users

TL;DR

This paper introduces a privacy-preserving protocol for face retrieval in cloud storage, enabling mobile users to search photos containing specific individuals without exposing their images or the face detector to the cloud provider.

Contribution

It presents a novel protocol that simultaneously protects user photos and face detector privacy during cloud-based face retrieval for mobile users.

Findings

Successfully retrieves relevant photos while preserving privacy.

Protects both user photos and face detector from cloud provider.

Effective in family and class scenarios.

Abstract

Recently, cloud storage and processing have been widely adopted. Mobile users in one family or one team may automatically backup their photos to the same shared cloud storage space. The powerful face detector trained and provided by a 3rd party may be used to retrieve the photo collection which contains a specific group of persons from the cloud storage server. However, the privacy of the mobile users may be leaked to the cloud server providers. In the meanwhile, the copyright of the face detector should be protected. Thus, in this paper, we propose a protocol of privacy preserving face retrieval in the cloud for mobile users, which protects the user photos and the face detector simultaneously. The cloud server only provides the resources of storage and computing and can not learn anything of the user photos and the face detector. We test our protocol inside several families and classes. The experimental results reveal that our protocol can successfully retrieve the proper photos from the cloud server and protect the user photos and the face detector.