ANONYMIZATION OF DATA USING MAPREDUCE ON CLOUD

Mallappa Gurav, N. V. Karekar, Manjunath Suryavanshi

Abstract: In computer world cloud services are provided by the service providers. The user wants to share the private data which are stored in cloud server for different reasons like data mining, data analysis etc. These can bring the privacy concern. Privacy preservation can be satisfied by Anonymizing data sets through generalization to satisfy privacy requirements by using kanonymity technique which is a widely used type of privacy preserving techniques. At present days the data of cloud applications are increasing their scale day by day concern with Big Data trend. So it is very difficult thing to accept, manage, maintain and process the large scaled data with-in the required time stamps. Thus for privacy preserving on privacy sensitive , large scaled data is very difficult task for existing anonymization techniques because they will not manage the scaled data sets. This approach addresses the anonymization problem on large scale cloud data sets using two phase top down specialization approach and MapReduce framework. Innovative MapReduce jobs are carefully designed in both phases of this technique to achieve specialization computation on scalable data sets. Scalability and efficiency of Top Down Specialization (TDS) is significantly increased over the existing approach.

Keywords: Top Down Specialization, MapReduce, Data Anonymization, Cloud Computing, Privacy Preservation

DOI: https://doi.org/10.15623/ijret.2015.0407021