Dynamic Data Sensitivity Access Control in Hadoop Platform

Smart technological innovations are exponentially generating big amounts of data leading to the need for new processing and storage technologies. Hadoop is the main Big Data platform. In the current implementation of Hadoop, only file-level access control and Access Control Lists (ACLs) are typically applied to data. Several researchers have investigated on data protection on Hadoop but the common concern was always to protect sensitive data. In order to address this issue, we propose a dynamic framework, which calculates data sensitivity in an automated way without any intervention of the Data Owner. Data sensitivity changes over the time depending on scenarios provided by our scalable framework in order to protect sensitive data as long as it resides in the Hadoop cluster with the aim to keep this data out of the reach of unauthorized users.