Automated extraction of attributes from natural language attribute-based access control (ABAC) Policies View Full Text


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Article Info

DATE

2019-12

AUTHORS

Manar Alohaly, Hassan Takabi, Eduardo Blanco

ABSTRACT

The National Institute of Standards and Technology (NIST) has identified natural language policies as the preferred expression of policy and implicitly called for an automated translation of ABAC natural language access control policy (NLACP) to a machine-readable form. To study the automation process, we consider the hierarchical ABAC model as our reference model since it better reflects the requirements of real-world organizations. Therefore, this paper focuses on the questions of: how can we automatically infer the hierarchical structure of an ABAC model given NLACPs; and, how can we extract and define the set of authorization attributes based on the resulting structure. To address these questions, we propose an approach built upon recent advancements in natural language processing and machine learning techniques. For such a solution, the lack of appropriate data often poses a bottleneck. Therefore, we decouple the primary contributions of this work into: (1) developing a practical framework to extract authorization attributes of hierarchical ABAC system from natural language artifacts, and (2) generating a set of realistic synthetic natural language access control policies (NLACPs) to evaluate the proposed framework. Our experimental results are promising as we achieved - in average - an F1-score of 0.96 when extracting attributes values of subjects, and 0.91 when extracting the values of objects’ attributes from natural language access control policies. More... »

PAGES

2

References to SciGraph publications

  • 2014. Mining Attribute-Based Access Control Policies from Logs in DATA AND APPLICATIONS SECURITY AND PRIVACY XXVIII
  • 2012. Information Extraction from Text in MINING TEXT DATA
  • 2016. Mining Hierarchical Temporal Roles with Multiple Metrics in DATA AND APPLICATIONS SECURITY AND PRIVACY XXX
  • 2015. Automatic Top-Down Role Engineering Framework Using Natural Language Processing Techniques in INFORMATION SECURITY THEORY AND PRACTICE
  • 2013-06. Evaluation of text document clustering approach based on particle swarm optimization in CENTRAL EUROPEAN JOURNAL OF COMPUTER SCIENCE
  • 1994-03. The Principle of Semantic Compositionality in TOPOI
  • 2015. HGABAC: Towards a Formal Model of Hierarchical Attribute-Based Access Control in FOUNDATIONS AND PRACTICE OF SECURITY
  • 2015. Evolutionary Inference of Attribute-Based Access Control Policies in EVOLUTIONARY MULTI-CRITERION OPTIMIZATION
  • 2017. Identification of Access Control Policy Sentences from Natural Language Policy Documents in DATA AND APPLICATIONS SECURITY AND PRIVACY XXXI
  • 2015-05. Deep learning in NATURE
  • Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1186/s42400-018-0019-2

    DOI

    http://dx.doi.org/10.1186/s42400-018-0019-2

    DIMENSIONS

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