Please use this identifier to cite or link to this item:
http://hdl.handle.net/10773/26472
Title: | BDFIS: Binary Decision access control model based on Fuzzy Inference Systems |
Author: | Regateiro, Diogo Domingues Pereira, Óscar Mortágua Aguiar, Rui L. |
Keywords: | Fuzzy systems Vague knowledge Information security Access control |
Issue Date: | 10-Jul-2019 |
Publisher: | KSI Research Inc. and Knowledge Systems Institute Graduate School |
Abstract: | Access control is a ubiquitous feature in almost all computer systems, and as data becomes more and more of an important asset for organizations, so do the associated access control policies. However, with the increase in the amount of data being produced, e.g. in IoT and social networks, the interest in simpler access control is increasing as well since more subjects (public, researchers, etc.) are now requesting access to it. Defining the exact conditions to allow each subject to access the data can be difficult, especially when vaguely defined conditions such as "expertise of a researcher" come into play. Fuzzy Inference Systems (FIS) allow to process these vague conditions and enables access control mechanisms to be more easily applied. The contribution of this paper lies in showing how a FIS can be used to output binary access control decisions (grant/deny) and what are the differences in the inference process that stems from restricting the output to these two output values. |
Peer review: | yes |
URI: | http://hdl.handle.net/10773/26472 |
DOI: | 10.18293/SEKE2019-039 |
ISBN: | 1-891706-48-9 |
ISSN: | 2325-9000 |
Appears in Collections: | DETI - Comunicações |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
SEKE2019_paper_39.pdf | 346.66 kB | Adobe PDF | View/Open |
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.