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Tools for Understanding Identity

Creese, Sadie, Gibson-Robinson, Thomas, Goldsmith, Michael, Hodges, Duncan, Kim, Dee, Love, Oriana, Nurse, Jason R. C., Pike, Bill, Schultz, Jean (2014) Tools for Understanding Identity. In: 2013 IEEE International Conference on Technologies for Homeland Security (HST). . IEEE E-ISBN 978-1-4799-1535-4. (doi:10.1109/THS.2013.6699064) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided) (KAR id:67520)

The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided.
Official URL:
https://doi.org/10.1109/THS.2013.6699064

Abstract

We present two tools for analysing identity in support of homeland security. Both are based upon the Superi-dentity model that brings together cyber and physical spaces into a single understanding of identity. Between them, the tools provide support for defensive, information gathering and capability planning operations. The first tool allows an analyst to explore and understand the model, and to apply it to risk-exposure assessment activities for a particular individual, e.g. an influential person in the intelligence or government community, or a commercial company board member. It can also be used to understand critical capabilities in an organization's identity-attribution process, and so used to plan resource investment. The second tool, referred to as Identity Map, is designed to support investigations requiring enrichment of identities and the making of attributions. Both are currently working prototypes.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/THS.2013.6699064
Subjects: Q Science
T Technology
Divisions: Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Computing
Divisions > Division of Computing, Engineering and Mathematical Sciences > School of Engineering and Digital Arts
Depositing User: Jason Nurse
Date Deposited: 02 Jul 2018 16:36 UTC
Last Modified: 05 Nov 2024 11:07 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/67520 (The current URI for this page, for reference purposes)

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