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.
2018
Di Cerbo, Francesco; Rosa, Marco
File allegato/i alla scheda:
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

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10446/133316
Citazioni
  • Scopus 0
  • ???jsp.display-item.citation.isi??? 0
social impact