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Understanding Insider Threat: A Framework for Characterising Attacks

Nurse, Jason R. C., Buckley, Oliver, Legg, Philip A., Goldsmith, Michael, Creese, Sadie, Wright, Gordon R.T., Whitty, Monica (2014) Understanding Insider Threat: A Framework for Characterising Attacks. In: 2014 IEEE Security and Privacy Workshops. . IEEE E-ISBN 978-1-4799-5103-1. (doi:10.1109/SPW.2014.38)

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https://doi.org/10.1109/SPW.2014.38

Abstract

The threat that insiders pose to businesses, institutions and governmental organisations continues to be of serious concern. Recent industry surveys and academic literature provide unequivocal evidence to support the significance of this threat and its prevalence. Despite this, however, there is still no unifying framework to fully characterise insider attacks and to facilitate an understanding of the problem, its many components and how they all fit together. In this paper, we focus on this challenge and put forward a grounded framework for understanding and reflecting on the threat that insiders pose. Specifically, we propose a novel conceptualisation that is heavily grounded in insider-threat case studies, existing literature and relevant psychological theory. The framework identifies several key elements within the problem space, concentrating not only on noteworthy events and indicators- technical and behavioural- of potential attacks, but also on attackers (e.g., the motivation behind malicious threats and the human factors related to unintentional ones), and on the range of attacks being witnessed. The real value of our framework is in its emphasis on bringing together and defining clearly the various aspects of insider threat, all based on real-world cases and pertinent literature. This can therefore act as a platform for general understanding of the threat, and also for reflection, modelling past attacks and looking for useful patterns.

Item Type: Conference or workshop item (Paper)
DOI/Identification number: 10.1109/SPW.2014.38
Subjects: B Philosophy. Psychology. Religion > BF Psychology
Q Science
T Technology
Divisions: Faculties > Sciences > School of Computing
Faculties > Sciences > School of Computing > Security Group
Faculties > Social Sciences > School of Psychology
Depositing User: Jason Nurse
Date Deposited: 02 Jul 2018 16:31 UTC
Last Modified: 01 Aug 2019 10:43 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/67518 (The current URI for this page, for reference purposes)
Nurse, Jason R. C.: https://orcid.org/0000-0003-4118-1680
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