Query Processing in Private Data Outsourcing Using Anonymization
The authors present a scheme for query processing in a private data outsourcing model. They assume that data is divided into identifying and sensitive data using an anatomy approach; only the client is able to reconstruct the original identifiable data. The key contribution of this paper is a relational query processor that minimizes the client-side computation while ensuring that the server learns nothing violating the privacy constraints. Data outsourcing is a growing business. Cloud computing developments such as Amazon Relational Database Service promise further reduced cost.