Abstract
In the current circumstance, the dimension of information in many kind of cloud atmosphere increases enormously along with the trend of Big Data. Subsequently making, it is a test for common software programming tools to get, supervise, and huge scale process information inside an explicit spans. Thus, it is a test for previous anonymization ways to agreement protection preservation on credential datasets because of their insufficiency of adaptability. To overcome these issues, efficient and Secure data balanced scheduling (ESDBS) algorithm is introduced to data maintain large-scale credential data sets using the MapReduce framework in big data aspects. The proposed system designs efficient MapReduce tasks to concretely achieve the specialization computation in a scalable manner. Based on the experimental evaluation, proposed ESDBS algorithm reduces 20 seconds encryption time and improves 15% algorithm efficiency and 6% system throughput compare than convention techniques.