An approach to provide security to unstructured Big Data

Abstract

Security of Big Data is a big concern. In broad sense Big Data contains two types of data such as structured and unstructured. To provide security to unstructured data is more difficult than that of structured. In this paper we have developed an approach to give adequate security to the unstructured data by considering the types of the data and their sensitivity levels. We have reviewed the different analytics methods of Big Data, which gives us the facility to build a data node of databases of different types of data. Each type of data has been further classified to provide adequate security and enhance the overhead of the security system. To provide security to data node a security suite has been designed by incorporating different security standards and algorithms. The proper security standards or algorithms can be activated using an algorithm, which has been interfaced with the data node. We have shown that data classification with respect to sensitivity levels enhance the performance of the system.