Secure and Efficient Query Processing Technique for Encrypted Databases in Cloud

Abstract

Cloud computing is an attractive environment for both organizations and individual users, as it provides scalable computing and storage services at an affordable price. However, privacy and confidentiality are two challenges that trouble most users. Data encryption, using a powerful encryption algorithm such as the Advanced Encryption Standard (AES), is one solution that can allay users' concerns, but other challenges with searching over encrypted data have arisen. Researchers have proposed many different schemes to execute Standard Query Language (SQL) queries over encrypted data by encrypting the data with more than one encryption algorithm. However, other researchers have proposed systems based on the fragmentation of encrypted data. In this paper, we propose bit vector-based model (BVM), a secure database system that works as an intermediary between users and the cloud provider. In BVM, before the encryption and outsourcing processes, the query manager (QM) takes each record from the main table, parses it, builds a bit vector for it, and stores it. The BV stores bits, zero and one, and its length equals the total number of sub-columns for all sensitive columns. BVM aims to reduce the range of retrieved encrypted records that are related to a user's query from the cloud. In our model, the cloud provider cannot deduce information from the encrypted data nor can infer which encryption algorithm was used to encrypt data. We implement BVM and run different experiments to compare our model with the methods in which data are not encrypted in the cloud. Our evaluation shows that BVM reduces the range of the retrieved encrypted records from the cloud to less than 35 percent of encrypted records. As a result, our model avoids unnecessary decryption processes that affect delay times.