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https://doi.org/10.1109/cic.20...
Article . 2016 . Peer-reviewed
Data sources: Crossref
https://dx.doi.org/10.13016/m2...
Other literature type . 2016
Data sources: Datacite
DBLP
Conference object
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Capturing Policies for Fine-Grained Access Control on Mobile Devices

Authors: Prajit Kumar Das; Anupam Joshi; Tim Finin;

Capturing Policies for Fine-Grained Access Control on Mobile Devices

Abstract

As of 2016, there are more mobile devices than humans on earth. Today, mobile devices are a critical part of our lives and often hold sensitive corporate and personal data. As a result, they are a lucrative target for attackers, and managing data privacy and security on mobile devices has become a vital issue. Existing access control mechanisms in most devices are restrictive and inadequate. They do not take into account the context of a device and its user when making decisions. In many cases, the access granted to a subject should change based on the context of a device. Such fine-grained, context-sensitive access control policies have to be personalized too. In this paper, we present a system i.e. Mithril that uses policies represented in Semantic Web technologies and captured using user feedback, to handle access control on mobile devices. We present an iterative feedback process to capture user specific policy. We also present a policy violation metric that allows us to decide when the capture process is complete.

2nd IEEE International Conference on Collaboration and Internet Computing (CIC 2016), Pittsburgh, PA, USA, November 1-3, 2016

Keywords

Measurement, data privacy, semantic Web, mobile computing, Context, Androids, policy violation metric, Context modeling, Access control, MITHRIL

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average