Title: Privacy Preserving Face Retrieval in the Cloud for Mobile Users,
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.