The paper presents an approach based on machine learning to refine attribute-based access control policies in order to reduce the risks of users abusing their privileges. The approach exploits behavioral patterns representing how users typically access resources to narrow the permissions granted to users when anomalous behaviors are detected.

Towards Adaptive Access Control

Paci, Federica;
2018-01-01

Abstract

The paper presents an approach based on machine learning to refine attribute-based access control policies in order to reduce the risks of users abusing their privileges. The approach exploits behavioral patterns representing how users typically access resources to narrow the permissions granted to users when anomalous behaviors are detected.
978-3-319-95728-9
access control, machine learning, insider threats, machine learning
File in questo prodotto:
File Dimensione Formato  
DBSEC.pdf

accesso aperto

Tipologia: Documento in Pre-print
Licenza: Creative commons
Dimensione 363.31 kB
Formato Adobe PDF
363.31 kB Adobe PDF Visualizza/Apri

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/992959
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 197
  • ???jsp.display-item.citation.isi??? ND
social impact