An Efficient Privacy-Preserving Search Technique for Encrypted Cloud Data

Abstract

In the present scenario of data management and computing, private data has been widely outsourced into cloud storage for its ability to provide low-cost access and maintenance services offered by public clouds such as Windows Azure, Google cloud platform, Amazon S3, IBM Bluemix, and so on for flexibility and economic benefits as well. Therefore, sensitive data such as Email, medical records, and other critical data assets must be kept in an encrypted form in order to preserve privacy and integrity of data. The major challenge in keeping encrypted data in cloud is that the searching process would be more complex. The data owner normally does not want the cloud provider to understand and analyze what has been done by the data owner and data user on the encrypted data in cloud storage. However, data owner and data user want to perform some computations on encrypted data such as sorting of records, splitting, searching, and ranking. This paper proposes a technique to perform search over encrypted data. When comes to performing, searching, and ranking on encrypted data, an algorithm which is mathematically strong is essential and it must be performed by the cloud provider without privacy leak. As a huge number of data users and data owners are maintaining large collection of documents in the cloud, it is essential to support multiple keyword searches in encrypted cloud data in order to present relevant documents with maximum accuracy and privacy preservation. The proposed technique for searching over encrypted data domain allows data users to search and rank according to the input query with less complexity in computation.