Key independent encrypted face clustering

In a cloud environment to preserve privacy of the end user, there arises a need to match and classify images in the encrypted domain. To impart granularity to image-data access it is important to make the matching process key independent, without compromising on the strength of the cipher or precision in the matching process. In this paper we propose a simple block intensity substitution as an encryption algorithm. The feature that remains transparent to this form of encryption is the sorted intensity histogram and its derivatives. These secondary and tertiary histogram based features remain robust to pose variations and yet discriminating across different subjects. A blind encrypted image classification procedure based on a standard unsupervised clustering algorithm has been used to validate the proposed concept.