Work in progress: K-nearest neighbors techniques for ABAC policies clustering

TitreWork in progress: K-nearest neighbors techniques for ABAC policies clustering
Publication TypeConference Paper
Year of Publication2016
AuthorsBenkaouz, Ya, Erradi, Ma, Freisleben, Bb
Conference NameABAC 2016 - Proceedings of the 2016 ACM International Workshop on Attribute Based Access Control, co-located with CODASPY 2016
Abstract

In this paper, we present an approach based on the K- Nearest Neighbors algorithms for policies clustering that aims to reduce the ABAC policies dimensionality for high scale systems. Since ABAC considers a very large set of attributes for access decisions, it turns out that using such model for large scale systems might be very complicated. To date, researchers have proposed to use data mining techniques to discover roles for RBAC system construction. In this work in progress, we consider the usage of KNN-based techniques for the classification of ABAC policies based on similarity computations of rules in order to enhance the ABAC exibility and to reduce the number of policy rules. © 2016 ACM.

URLhttps://www.scopus.com/inward/record.uri?eid=2-s2.0-84966549589&doi=10.1145%2f2875491.2875497&partnerID=40&md5=2378f9f3208a82bfc833b26f1a7ef267
DOI10.1145/2875491.2875497
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