A full-text retrieval algorithm for encrypted data in cloud storage applications

Abstract

Nowadays, more and more Internet users use the cloud storage services to store their personal data, especially when the mobile devices which have limited storage capacity popularize. With the cloud storage services, the users can access their personal data at any time and anywhere without storing the data at local. However, the cloud storage service provider is not completely trusted. Therefore, the first concern of using cloud storage services is the data security. A straightforward method to address the security problem is to encrypt the data before uploading to the cloud server. The encryption method is able to keep the data secret from the cloud server, but cloud server also can not manipulate the data after encryption. It will greatly undermine the advantage of the cloud storage. For example, a user encrypts his personal data before uploading them to the cloud. When he wants to access some data at the cloud, he has to download all the data and decrypt them. Obviously, this service mode will incur the huge overheads of communication and computation. Several related works have been proposed to enable the search over the encrypted data, but all of them only support the encrypted keyword search. In this paper, we propose a new full-text retrieval algorithm over the encrypted data for the scenario of cloud storage, in which all the words in a document have been extracted and built a privacy-preserved full-text retrieval index. Based on the privacy-preserved full-text retrieval index, cloud server can execute full-text retrieval over the large scale encrypted documents. The numerical analysis and experimental results further validate the high efficiency and scalability of the proposed algorithm.