Privacy-Enhanced Data Deduplication Computational Intelligence Technique for Secure Healthcare Applications

Abstract

A significant number of cloud storage environments are already implementing deduplication technology. Due to the nature of the cloud environment, a storage server capable of accommodating large-capacity storage is required. As storage capacity increases, additional storage solutions are required. By leveraging deduplication, you can fundamentally solve the cost problem. However, deduplication poses privacy concerns due to the structure itself. In this paper, we point out the privacy infringement problem and propose a new deduplication technique to solve it. In the proposed technique, since the user's map structure and files are not stored on the server, the file uploader list cannot be obtained through the server's meta-information analysis, so the user's privacy is maintained. In addition, the personal identification number (PIN) can be used to solve the file ownership problem and provides advantages such as safety against insider breaches and sniffing attacks. The proposed mechanism required an additional time of approximately 100 ms to add a IDRef to distinguish user-file during typical deduplication, and for smaller file sizes, the time required for additional operations is similar to the operation time, but relatively less time as the file's capacity grows.