Abstract
Big data analytics allows to obtain valuable information from different data sources. It is important to maintain control of those data because unauthorised copies could be used by other entities or companies interested in them. Hadoop is widely used for processing large volumes of information and therefore is ideal for developing big data applications. Its security model focuses on the control within a cluster by preventing unauthorised users, or encrypting data distributed among nodes. Sometimes, data theft is carried out by personnel who have access to the system so they can skip most of the security features. In this paper, we present an extension to the Hadoop security model that lets control the information from the source, avoiding that data can be used by unauthorised users and improving corporative e-governance. We use an eToken with elliptic curve cryptography that performs a robust operation of the system and prevents from being falsified, duplicated or manipulated.
A.F. Díaz—This work has been partially supported by European Union FEDER and the Spanish Ministry of Economy and Competitiveness TIN2015-67020-P, FPA2015-65150-C3-3-P, and PROMEP/103.5/13/6475 UAEH-146.
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Díaz, A.F., Blokhin, I., Ortega, J., Palacios, R.H., Rodríguez-Quintana, C., Díaz-García, J. (2016). Secure Data Access in Hadoop Using Elliptic Curve Cryptography. In: Carretero, J., et al. Algorithms and Architectures for Parallel Processing. ICA3PP 2016. Lecture Notes in Computer Science(), vol 10049. Springer, Cham. https://doi.org/10.1007/978-3-319-49956-7_11
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