Designing a Bit-Based Model to Accelerate Query Processing Over Encrypted Databases in Cloud

Database users have started moving toward the use of cloud computing as a service because it provides computation and storage needs at affordable prices. However, for most of the users, the concern of privacy plays a major role as they cannot control data access once their data are outsourced, especially if the cloud provider is curious about their data. Data encryption is an effective way to solve privacy concerns, but executing queries over encrypted data is a problem that needs attention. In this research, we introduce a bit-based model to execute different relational algebra operators over encrypted databases at the cloud without decrypting the data. To encrypt data, we use the randomized encryption algorithm (AES-CBC) to provide the maximum-security level. The idea is based on classifying attributes as sensitive and non-sensitive, where only sensitive attributes are encrypted. For each sensitive attribute, the table’s owner predefines the possible partition domains on which the tuples will be encoded into bit vectors before the encryption. We store the bit vectors in an additional column in the encrypted table in the cloud. We use those bits to retrieve only part of encrypted records that are candidates for a specific query. We implemented and evaluated our model and found that the proposed model is practical and success to minimize the range of the retrieved encrypted records to less than 30% of the whole set of encrypted records in a table.