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Access Control for XML Big Data Applications

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Encyclopedia of Complexity and Systems Science

Abstract

Big data has become a widespread concept in domains such as law enforcement, health care, e-commerce, and national defense. These and other big data applications have complex security requirements that need to be defined, realized, and enforced in order to facilitate the workflow of users that need access to these big data repositories. As such, security assurance emerges as an important requirement when considering access control, security privileges, and their enforcement over time as users interact with the big data applications. Taking into consideration the increase in database as a service (DaaS), solutions that work toward abstracting the big data repositories can be facilitated by utilizing the eXtensible Markup Language, XML. XML has emerged as one of the de facto standards of information that has seen increasing and significant usage in the exchange between these repositories and the big data applications. In this entry, we present a case study in the domain of law enforcement that considers a big data source, the Crash Data Repository, and the need to provide access control for the information found within. By using extensions to the Unified Modeling Language (UML) to model document (XML) schemas and the security requirements tied to the information validated by the schemas, we achieve security assurance a big data repository represented in XML. This model security is accompanied via automatic policy generation that covers Mandatory, Role-Based and Discretionary Access Control (MAC, RBAC, and DAC, respectively) requirements. As a result, we enable the development of secure big data applications that use XML as their document format.

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Correspondence to Alberto De la Rosa Algarin .

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De la Rosa Algarin, A., Demurjian, S.A., Jackson, E. (2021). Access Control for XML Big Data Applications. In: Meyers, R.A. (eds) Encyclopedia of Complexity and Systems Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-27737-5_756-1

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  • DOI: https://doi.org/10.1007/978-3-642-27737-5_756-1

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  • Print ISBN: 978-3-642-27737-5

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