Abstract
Recently, database users have begun to use cloud database services to outsource their databases. The reason for this is the high computation speed and the huge storage capacity that cloud owners provide at low prices. However, despite the attractiveness of the cloud computing environment to database users, privacy issues remain a cause for concern for database owners since data access is out of their control. Encryption is the only way of assuaging users' fears surrounding data privacy, but executing Structured Query Language (SQL) queries over encrypted data is a challenging task, especially if the data are encrypted by a randomized encryption algorithm. Many researchers have addressed the privacy issues by encrypting the data using deterministic, onion layer, or homomorphic encryption. Nevertheless, even with these systems, the encrypted data can still be subjected to attack. In this research, we first propose an indexing scheme to encode the original table's tuples into bit vectors (BVs) prior to the encryption. The resulting index is then used to narrow the range of retrieved encrypted records from the cloud to a small set of records that are candidates for the user's query. Based on the indexing scheme, we then design a system to execute SQL queries over the encrypted data. The data are encrypted by a single randomized encryption algorithm, namely the Advanced Encryption Standard-Cipher-Block Chaining (AES-CBC). In the proposed scheme, we store the index values (BVs) at user's side, and we extend the system to support most of relational algebra operators, such as select, join, etc. Implementation and evaluation of the proposed system reveals that it is practical and efficient at reducing both the computation and space overhead when compared with state-of-the-art systems like CryptDB.