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Geo-social-rbac: A location-based socially aware access control framework

Baracaldo, N and Palanisamy, B and Joshi, J (2014) Geo-social-rbac: A location-based socially aware access control framework. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8792. 501 - 509. ISSN 0302-9743

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Abstract

© Springer International Publishing Switzerland 2014. The ubiquity of low-cost GPS-enabled mobile devices and the proliferation of online social networks have enabled the collection of rich geo-social information that includes the whereabouts of the users and their social connections. This information can be used to provide a rich set of access control policies that ensure that resources are utilized securely. Existing literature focuses on providing access control systems that control the access solely based on either the location of the users or their social connections. In this paper, we argue that a number of real-world applications demand an access control model that effectively captures both the geographic as well as the social dimensions of the users in a given location. We propose, Geo-social-RBAC, a new role based access control model that allows the inclusion of geo-social constraints as part of the access control policy. Our model, besides capturing the locations of a user requesting access and her social connections, includes geo-social cardinality constraints that dictate how many people related by a particular social relation need to be present in the required locations at the time of an access. The model also allows specification of geo-social and location trace constraints that may be used to dictate if an access needs to be granted or denied.


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Details

Item Type: Article
Status: Published
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Baracaldo, N
Palanisamy, Bbpalan@pitt.eduBPALAN
Joshi, Jjjoshi@pitt.eduJJOSHI
Date: 1 January 2014
Date Type: Publication
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Journal or Publication Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume: 8792
Page Range: 501 - 509
Event Type: Conference
Institution: University of Pittsburgh
Schools and Programs: School of Information Sciences > Information Science
Refereed: No
ISBN: 9783319116976
ISSN: 0302-9743
Date Deposited: 24 Jun 2014 19:48
Last Modified: 01 Nov 2017 12:58
URI: http://d-scholarship.pitt.edu/id/eprint/22067

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