%0 Conference Proceedings
%T Mining Attribute-Based Access Control Policies from Logs
%+ Stony Brook University [SUNY] (SBU)
%A Xu, Zhongyuan
%A Stoller, Scott, D.
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 28th IFIP Annual Conference on Data and Applications Security and Privacy (DBSec)
%C Vienna, Austria
%Y David Hutchison
%Y Takeo Kanade
%Y Bernhard Steffen
%Y Demetri Terzopoulos
%Y Doug Tygar
%Y Gerhard Weikum
%Y Vijay Atluri
%Y Günther Pernul
%Y Josef Kittler
%Y Jon M. Kleinberg
%Y Alfred Kobsa
%Y Friedemann Mattern
%Y John C. Mitchell
%Y Moni Naor
%Y Oscar Nierstrasz
%Y C. Pandu Rangan
%I Springer
%3 Data and Applications Security and Privacy XXVIII
%V LNCS-8566
%P 276-291
%8 2014-07-14
%D 2014
%R 10.1007/978-3-662-43936-4_18
%Z Computer Science [cs]Conference papers
%X Attribute-based access control (ABAC) provides a high level of flexibility that promotes security and information sharing. ABAC policy mining algorithms have potential to significantly reduce the cost of migration to ABAC, by partially automating the development of an ABAC policy from information about the existing access-control policy and attribute data. This paper presents an algorithm for mining ABAC policies from operation logs and attribute data. To the best of our knowledge, it is the first algorithm for this problem.
%G English
%Z TC 11
%Z WG 11.3
%2 https://inria.hal.science/hal-01284862/document
%2 https://inria.hal.science/hal-01284862/file/978-3-662-43936-4_18_Chapter.pdf
%L hal-01284862
%U https://inria.hal.science/hal-01284862
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC11
%~ IFIP-LNCS-8566
%~ IFIP-WG11-3