Abstract
Big Data often refers to a set of technologies that process large volumes of heterogeneous data. “Data Security” and “Data Quality” are two essential aspects of any data-centric project. On the one hand, Data Security System aims to protect the Confidentiality, Integrity and Availability of data. On the other hand, Data Quality Management System ensures the monitoring, evaluation and improvement of many data characteristics such as Accuracy, Consistency, Completeness and Freshness. Much research has pointed out that these two systems, Security and Quality, can be mutually blocked. Assessing or improving data quality may require extended read and/or write access to the data which may not be permitted by the security policies. In this paper, we demonstrate that it is possible to use security systems to improve data quality thanks to a dynamic access control framework dedicated to collaborative and distributed environments. Our solution consists in extending the PolyOrBAC framework, initially designed to control access in collaborative platforms, to make it a dynamic data distribution platform. Thanks to this new architecture, it will be possible to eliminate duplicates in distributed and big data environments, reduce the amount of data and improve its quality.
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Talha, M., Abou El Kalam, A. (2022). Big Data: Towards a Collaborative Security System at the Service of Data Quality. In: Abraham, A., et al. Hybrid Intelligent Systems. HIS 2021. Lecture Notes in Networks and Systems, vol 420. Springer, Cham. https://doi.org/10.1007/978-3-030-96305-7_55
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