Protecting Private Information by Data Separation in Distributed Spatial Data Warehouse

Abstract

Both transactional and analytical systems store data, which being accessible to unauthorized persons may result in privacy violation. This issue has become especially important nowadays, due to more restrictive legislation concerning personal data protection and preserving data privacy. We introduce relation decomposition as a method to preserve the data confidentiality in distributed spatial data warehouses. Data separation between nodes of distributed system can easily protect data privacy without requiring encrypting sensitive data. Using the relation decomposition strongly reduces the possibility of a disclosure of private information contained in data warehouse. The article presents how specified secure policy can be implemented into the data warehouse system as well as how analytical applications can retrieve protected data from the database. Finally, we present test results verifying efficiency of the latter operations including comparison between relation decomposition and the most popular method of preserving data privacy i.e., data encryption using symmetric encryption algorithms