  Content-based image retrieval (CBIR) is one of the fundamental image
retrieval primitives. Its applications can be found in various areas, such as
art collections and medical diagnoses. With an increasing prevalence of cloud
computing paradigm, image owners desire to outsource their images to cloud
servers. In order to deal with the risk of privacy leakage of images, images
are typically encrypted before they are outsourced to the cloud, which makes
CBIR an extremely challenging task. Existing studies focus on the scenario with
only a single image owner, leaving the problem of CBIR with multiple image
sources (i.e., owners) unaddressed. In this paper, we propose a secure CBIR
scheme that supports Multiple Image owners with Privacy Protection (MIPP). We
encrypt image features with a secure multi-party computation technique, which
allows image owners to encrypt image features with their own keys. This enables
efficient image retrieval over images gathered from multiple sources, while
guaranteeing that image privacy of an individual image owner will not be leaked
to other image owners. We also propose a new method for similarity measurement
of images that can avoid revealing image similarity information to the cloud.
Theoretical analysis and experimental results demonstrate that MIPP achieves
retrieval accuracy and efficiency simultaneously, while preserving image
privacy.
