A probabilistic bound on the Basic Role Mining Problem and its applications

Alessandro Colantonio, Roberto di Pietro, Alberto Ocello, Nino Vincenzo Verde

Research output: Chapter in Book/Report/Conference proceedingConference contribution

20 Scopus citations

Abstract

The aim of this paper is to describe a new probabilistic approach to the role engineering process for RBAC. We address the issue of minimizing the number of roles, problem known in literature as the Basic Role Mining Problem (basicRMP). We leverage the equivalence of the above issue with the vertex coloring problem. Our main result is to prove that the minimum number of roles is sharply concentrated around its expected value. A further contribution is to show how this result can be applied as a stop condition when striving to find out an approximation for the basicRMP. The proposal can be also used to decide whether it is advisable to undertake the efforts to renew a RBAC state. Both these applications can result in a substantial saving of resources. A thorough analysis using advanced probabilistic tools supports our results. Finally, further relevant research directions are highlighted. © IFIP International Federation for Information Processing 2009.
Original languageEnglish (US)
Title of host publicationIFIP Advances in Information and Communication Technology
PublisherSpringer New York LLCbarbara.b.bertram@gsk.com
Pages376-386
Number of pages11
ISBN (Print)9783642012433
DOIs
StatePublished - Jan 1 2009
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-20

ASJC Scopus subject areas

  • Information Systems and Management

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