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Journal of Cybersecurity
Article . 2020 . Peer-reviewed
License: OUP Standard Publication Reuse
Data sources: Crossref
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Journal of Cybersecurity
Article
License: CC BY NC ND
Data sources: UnpayWall
DBLP
Article . 2020
Data sources: DBLP
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Categorizing human phishing difficulty: a Phish Scale

Authors: Michelle Steves; Kristen K. Greene; Mary Theofanos;

Categorizing human phishing difficulty: a Phish Scale

Abstract

Abstract As organizations continue to invest in phishing awareness training programs, many chief information security officers (CISOs) are concerned when their training exercise click rates are high or variable, as they must justify training budgets to organization officials who question the efficacy of awareness training when click rates are not declining. We argue that click rates should be expected to vary based on the difficulty of the phishing email for a target audience. Past research has shown that when the premise of a phishing email aligns with a user’s work context, it is much more challenging for users to detect a phish. Given this, we propose a Phish Scale, so CISOs and phishing training implementers can easily rate the difficulty of their phishing exercises and help explain associated click rates. We base our scale on past research in phishing cues and user context, and apply the scale to previously published and new data from enterprise-based phishing exercises. The Phish Scale performed well with the current phishing dataset, but future work is needed to validate it with a larger variety of phishing emails. The Phish Scale shows great promise as a tool to help frame data sharing on phishing exercise click rates across sectors.

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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!
32
Top 10%
Top 10%
Top 10%
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