Big Data Security: A Progress Study of Current User Authentication Schemes

In the past few years, a rapid evolution in the ICTs has been witnessed in various aspects, leading to a higher communication volume, and data exchange. `Big Data' is one of the recent paradigms, which comes into the picture as a result of such ever-growing technologies, characterizing the huge amounts of heterogeneous datasets generated from a large number of connected systems, and describing various techniques, and strategies designed to handle such datasets. However, data security has gained a major attention in the `Big Data' environment, where a massive data have to be accessed, processed, and exchanged between millions of heterogeneous devices all around the world. User authentication is one of the data security aspects which plays a significant role in protecting data and ensuring that only authorized entity can gain access to the shared data and related services. Recently, a number of authentication schemes have been developed to protect information transferred over insecure public channels in the big data systems. In this paper, we explore user authentication issues in big data environments, presenting some of the major authentication frameworks proposed recently for the same. First, we briefly define the user authentication strategy in terms of big data paradigm; then we investigate a number of authentication schemes exist in literature and highlight their main contributions. Finally, we provide a relative comparison of these schemes, presenting their authentication models, methodologies, key advantages and potential limitations.