• cloud computing;
  • privacy-preserved data query;
  • service-oriented query;
  • two stage index


As cloud computing becomes prevalent, more and more sensitive information are being centralized into the cloud. A basic methodology that may address cloud data privacy issue is to encrypt the data before outsourcing. However, this makes effective data utilization, for example, searching a very challenging task. Although some searchable encryption schemes have been proposed to allow a user to search over encrypted data, these techniques are extremely difficult to provide efficient encrypted data query with various service patterns such as nonuniform data distribution, nonuniform query workload, and attributes join query. In this paper, we research efficient privacy-preserved data query methodologies for querying cipher-text numeric relational data in cloud computing. To provide efficient relational data query service just as DBMS does through SQL, we propose a service-oriented query (SOQ) algorithm that adaptively adjusts the encrypted data buckets based on sensitive data distribution and query workload. Moreover, we propose a two-stage index to address the issue of join query between encrypted attributes that has not been well solved to our knowledge. We design experiments to evaluate performances of our schemes and algorithms, which show that our methods achieve satisfactory encrypted data query performances. Copyright © 2013 John Wiley & Sons, Ltd.