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.
(2018). Bringing Access Control Tree to Big Data . Retrieved from http://hdl.handle.net/10446/133316
Bringing Access Control Tree to Big Data
Rosa, Marco
2018-01-01
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.File | Dimensione del file | Formato | |
---|---|---|---|
dcr-etaa.pdf
Solo gestori di archivio
Versione:
postprint - versione referata/accettata senza referaggio
Licenza:
Licenza default Aisberg
Dimensione del file
292.61 kB
Formato
Adobe PDF
|
292.61 kB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
Aisberg ©2008 Servizi bibliotecari, Università degli studi di Bergamo | Terms of use/Condizioni di utilizzo