Mondrian Based Real Time Anonymization Model

The presence of private information belonging to individuals in data heaps called "Big Data" causes the privacy person be endangered against disclosure attacks. To protect personal big data, it is ensured that anonymous created, stored, and shared systems with anonymization methods. However, de-identified cannot reinstatement. aim this study create a new method provides instant disidentification does not disrupt structure system. In study, Hadoop ecosystem was used process large heaps. With proposed model, has been requests from user are processed services middle layer, thus obtaining data. algorithm for optimized results compared according algorithms literature. observed user-friendly terms querying an set. According analysis results, works 40% efficiency other processing speed created model.