The 23rd International Conference on Information Integration and Web Intelligence 2021
DOI: 10.1145/3487664.3487789
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Extended XACML Language and Architecture for Access Control in Graph-structured Data

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Cited by 1 publication
(2 citation statements)
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“…Mohamed et al (2021) coupled ABAC with a new declarative language for fine-grained, attribute-based authorization policy, named XACML for Graph-structured data (XACML4G) . The same authors proposed an extension to the XACML language and architecture in Mohamed et al (2022) to specify and enforce fine-grained constraints on graph paths. Even though additional path-specific constraints in terms of graph patterns can be described, the policy rules require specialized processing and the enforcement mechanism needs to be adapted to work in a specific graph datastore (Sicari et al , 2022).…”
Section: Graph Databasesmentioning
confidence: 99%
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“…Mohamed et al (2021) coupled ABAC with a new declarative language for fine-grained, attribute-based authorization policy, named XACML for Graph-structured data (XACML4G) . The same authors proposed an extension to the XACML language and architecture in Mohamed et al (2022) to specify and enforce fine-grained constraints on graph paths. Even though additional path-specific constraints in terms of graph patterns can be described, the policy rules require specialized processing and the enforcement mechanism needs to be adapted to work in a specific graph datastore (Sicari et al , 2022).…”
Section: Graph Databasesmentioning
confidence: 99%
“…The established policy language and access control model eXtensible Access Control Markup Language (XACML) [2], for example, supports separation of concerns. In addition, in research prototypes like the ones presented by Bertino et al (2001), Colombo and Ferrari (2017), Kacimi and Benhlima (2017), Bogaerts et al (2017) and Mohamed et al (2022), authorization policy management and enforcement are also independent of the application and the underlying datastore. However, there are still many integrated and platform-dependent approaches.…”
Section: Separation Of Concerns (R5)mentioning
confidence: 99%