Query Processing in Private Data Outsourcing Using Anonymization

Abstract Data outsourcing is a growing business. Cloud computing developments such as Amazon Relational Database Service promise further reduced cost. However, use of such a service can be constrained by privacy laws, requiring specialized service agreements and data protection that could reduce economies of scale and dramatically increase costs. We propose a private data outsourcing approach where the link between identifying information and sensitive (protected) information is encrypted, with the ability to decrypt this link residing only with the client. As the server no longer has access to individually identifiable protected information, it is not subject to privacy laws, and can offer a service that does not need to be customized to the needs of each country- or sector-specific requirements; any risk of violating privacy through releasing sensitive information tied to an individual remains with the client. The data model used in this work is shown with an example in Figure 1. This work presents a re...