Data Anonymization Using Map Reduce On Cloud

Abstract

In this paper, we propose a scalable two-phase top-down specialization (TDS) approach to anonymize large-scale data sets using the Map Reduce framework on cloud. In both phases of our approach, we deliberately design a group of innovative Map Reduce jobs to concretely accomplish the specialization computation in a highly scalable way. Experimental evaluation results demonstrate that with our approach, the scalability and efficiency of TDS can be significantly improved over existing approaches.
KEYWORDS: Data anonymization; top-down specialization; MapReduce; cloud; privacy preservation