Big Data Security and Privacy: New Proposed Model of Big Data with Secured MR Layer

Abstract

The publication and dispersal of crude information are urgent components in business, scholarly, and restorative applications. With an expanding number of open stages, for example, informal communities and cell phones from which information might be gathered; the volume of such information have likewise expanded after some time progressed toward becoming as Big Data. The traditional model of Big Data does not specify any level for capturing the sensitivity of data both structured and combined. It additionally needs to incorporate the notion of privacy and security where the risk of exposing personal information is probabilistically minimized. This paper introduced security and privacy layer between HDFS and MR Layer (MapReduce) known as new proposed Secured MapReduce (SMR) Layer and this model is known as SMR model. The core benefit of this work is to promote data sharing for knowledge mining. This model creates a privacy and security guarantee and data utility for data miners. In this model, running time, CPU usage, Memory usage, and Information loss are less as compared to traditional approaches.