Abstract
Big data architectures bring advantages in terms of analytics performances and data storage. However the scarce availability of highly expressive declarative mechanisms for access control limits certain business and technical possibilities. This paper reports on the extension and adaptation of Access Control Tree to support effective decision making processes especially in evaluating multiple data policies for large data sets. An initial evaluation is also presented to evaluate the applicability of the extensions to big data use cases.
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Acknowledgements
This work was partly supported by EU-funded H2020 project C3ISP [grant no. 700294].
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Di Cerbo, F., Rosa, M. (2018). Bringing Access Control Tree to Big Data. In: Saracino, A., Mori, P. (eds) Emerging Technologies for Authorization and Authentication. ETAA 2018. Lecture Notes in Computer Science(), vol 11263. Springer, Cham. https://doi.org/10.1007/978-3-030-04372-8_2
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DOI: https://doi.org/10.1007/978-3-030-04372-8_2
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