Extending XACML Access Control Architecture for Allowing Preference-Based Authorisation

Kounga, Gina; Mont, Marco Casassa; Bramhall, Pete

doi:10.1007/978-3-642-15152-1_14

Cited by 3 publications

(3 citation statements)

References 5 publications

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“…Kounga et. al [12] proposed an extended architecture for allowing users to define authorization policies based on their preferences to allow or deny access to their private data. Helil et.…”

Section: Related Workmentioning

confidence: 99%

“…One reason for this, could be found in the fact that provenance data are stored in relational databases or RDF stores, with the access control left to the security mechanisms provided by these technologies. Security for database technologies has been extensively studied in the past (see [8] for an overview) and the increasing need for maintaining semantic resources has developed a large set of works focused on security for RDF data [9,10,11,12,13,14,15,16,17,18,19].…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Access control and view generation for provenance graphs

Dánger

Ćurčin

Missier

et al. 2015

Future Generation Computer Systems

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Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Access control and view generation for provenance graphs

Dánger

Ćurčin

Missier

et al. 2015

Future Generation Computer Systems

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“…Specific policies for provenance data can be implemented either by using either a dedicated provenance access control language [54,55,56], or an existing standard such as OASIS eXtensible Access Control Markup Language (XACML). Since XACML is not generally suitable for RDF data [57,54,58,59,60], extensions to it are necessary [61,60].…”

Section: Securitymentioning

confidence: 99%

Implementing interoperable provenance in biomedical research

Ćurčin

Miles

Dánger

et al. 2014

Future Generation Computer Systems

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The provenance of a piece of data refers to knowledge about its origin, in terms of entities and actors involved in its creation, e.g. data sources used, operations carried out on them, and users enacting those operations. Provenance is used to better understand the data and the context of its production, and to assess its reliability, by asserting whether correct procedures were followed. Providing evidence for validating research is of particular importance in the biomedical domain, where the strength of the results depends on the data sources and processes used. In recent times, previously manual processes have become fully or semi-automated, e.g. clinical trial recruitment, epidemiological studies, diagnosis making. The latter is typically achieved through interactions of heterogeneous software systems in multiple settings (hospitals, clinics, academic and industrial research organisations). Provenance traces of these software need to be integrated in a consistent and meaningful manner, but since these software systems rarely share a common platform, the provenance interoperability between them has to be achieved on the level of conceptual models. It is a non-trivial matter to determine where to start in making a biomedical software system provenance-aware. In this paper, we specify recommendations to developers on how to approach provenance modelling, capture, security, storage and querying, based on our expe- * riences with two large-scale biomedical research projects: Translational Research and Patient Safety in Europe (TRANSFoRm) and Electronic Health Records for Clinical Research (EHR4CR). While illustrated with concrete issues encountered, the recommendations are sufficiently high level so as to be reusable across the biomedical domain.

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The $$\mathrm {GURA_G}$$ GURA G Administrative Model for User and Group Attribute Assignment

Gupta

Sandhu

2016

Network and System Security

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Extending XACML Access Control Architecture for Allowing Preference-Based Authorisation

Cited by 3 publications

References 5 publications

Access control and view generation for provenance graphs

Access control and view generation for provenance graphs

Implementing interoperable provenance in biomedical research

The $$\mathrm {GURA_G}$$ GURA G Administrative Model for User and Group Attribute Assignment

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