A Framework for Attribute-Based Access Control in Processing Big Data with Multiple Sensitivities

There is an increasing demand for processing large volumes of unstructured data a wide variety applications. However, protection measures these big sets are still in their infancy, which could lead to significant security and privacy issues. Attribute-based access control (ABAC) provides dynamic flexible solution that effective mediating access. We analyzed implemented prototype application ABAC dataset Amazon Web Services, using open-source versions Apache Hadoop, Ranger, Atlas. The Hadoop ecosystem one the most popular frameworks storage adopted by major cloud service providers. conducted rigorous analysis cybersecurity implementing policies including developing synthetic information at multiple sensitivity levels realistically represents healthcare connected social media data. then developed Spark programs extract, connect, transform manner representative realistic use case. Our result framework securing Applying this ensures serious concerns addressed. provide details our experimentation code GitHub repository further research community.