Efficiently secure data privacy on hybrid cloud

Abstract

The growing concerns about the privacy of data stored in public cloud have hindered the widespread adoption of cloud. On one hand, large part of data, such as medical data, has a lot of images, and this kind of data may be private. On the other hand, the cloud service providers have the full access of data, and they may bleach the data for financial or other reasons. The traditional method to protect the privacy of data is to employ cryptographic algorithms, which unavoidably introduces heavy computation. Another way is hybrid cloud consisting of public and private cloud. The sensitive data is separated from non-sensitive data, and only the non-sensitive data is outsourced to public cloud. If we use hybrid cloud method directly, all the private images have to be stored in private cloud, which makes the adoption of cloud computing meaningless. Besides achieving data privacy, we should reduce computation and storage overhead in private cloud, as well as communication overhead between private and public cloud. In this paper, we propose a novel scheme to achieve the above goals. We test our scheme in real network environments (including Amazon EC2). We also propose a novel algorithm to process private image data. Our experimental results show that: (1) Our algorithm achieves data privacy but only takes about 1/1,000 the time of the AES algorithm. (2) The delay of our hybrid cloud approach (including the private and public cloud communications) is only 3%-5% more compared to the traditional public-cloud-only approach.