MailTrout: a machine learning browser extension for detecting phishing emails

Paul Boyle; Lynsay A. Shepherd

doi:10.14236/ewic/HCI2021.10

MailTrout: a machine learning browser extension for detecting phishing emails

Paul Boyle, Lynsay A. Shepherd^*

^*Corresponding author for this work

Department of Cybersecurity and Computing

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

5 Citations (Scopus)

2391 Downloads (Pure)

Abstract

The onset of the COVID-19 pandemic has given rise to an increase in cyberattacks and cybercrime, particularly with respect to phishing attempts. Cybercrime associated with phishing emails can significantly impact victims, who may be subjected to monetary loss and identity theft. Existing anti-phishing tools do not always catch all phishing emails, leaving the user to decide the legitimacy of an email. The ability of machine learning technology to identify reoccurring patterns yet cope with overall changes complements the nature of anti-phishing techniques, as phishing attacks may vary in wording but often follow similar patterns. This paper presents a browser extension called MailTrout, which incorporates machine learning within a usable security tool to assist users in detecting phishing emails. MailTrout demonstrated high levels of accuracy when detecting phishing emails and high levels of usability for end-users.

Original language	English
Title of host publication	34th British Human Computer Interaction Conference 2021 proceedings
Subtitle of host publication	"Post-pandemic HCI – Living digitally"
Editors	Jose Abdelnour Nocera, Helen Petrie, Gavin Sim, Torkil Clemmensen, Fotios Spyridonis
Publisher	BCS Learning & Development Ltd.
Pages	104-115
Number of pages	12
DOIs	https://doi.org/10.14236/ewic/HCI2021.10
Publication status	Published - 1 Jul 2021
Event	34rd British Human Computer Interaction Conference: Post-Pandemic HCI – Living digitally - University of West London, London, United Kingdom Duration: 19 Jul 2021 → 21 Jul 2021 Conference number: 34rd https://hci2021.bcs.org/

Publication series

Name	Electronic Workshops in Computing
Publisher	BCS Learning & Development
ISSN (Print)	1477-9358

Conference

Conference	34rd British Human Computer Interaction Conference
Country/Territory	United Kingdom
City	London
Period	19/07/21 → 21/07/21
Internet address	https://hci2021.bcs.org/

Keywords

Human-Computer Interaction
Machine Learning
Usable Security
Phishing

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.14236/ewic/HCI2021.10Licence: CC BY

Shepherd_MailTrout_Published_2021Final published version, 442 KBLicence: CC BY

Cite this

Boyle, P., & Shepherd, L. A. (2021). MailTrout: a machine learning browser extension for detecting phishing emails. In J. A. Nocera, H. Petrie, G. Sim, T. Clemmensen, & F. Spyridonis (Eds.), 34th British Human Computer Interaction Conference 2021 proceedings: "Post-pandemic HCI – Living digitally" (pp. 104-115). (Electronic Workshops in Computing). BCS Learning & Development Ltd.. https://doi.org/10.14236/ewic/HCI2021.10

Boyle, Paul ; Shepherd, Lynsay A. / MailTrout : a machine learning browser extension for detecting phishing emails. 34th British Human Computer Interaction Conference 2021 proceedings: "Post-pandemic HCI – Living digitally". editor / Jose Abdelnour Nocera ; Helen Petrie ; Gavin Sim ; Torkil Clemmensen ; Fotios Spyridonis. BCS Learning & Development Ltd., 2021. pp. 104-115 (Electronic Workshops in Computing).

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abstract = "The onset of the COVID-19 pandemic has given rise to an increase in cyberattacks and cybercrime, particularly with respect to phishing attempts. Cybercrime associated with phishing emails can significantly impact victims, who may be subjected to monetary loss and identity theft. Existing anti-phishing tools do not always catch all phishing emails, leaving the user to decide the legitimacy of an email. The ability of machine learning technology to identify reoccurring patterns yet cope with overall changes complements the nature of anti-phishing techniques, as phishing attacks may vary in wording but often follow similar patterns. This paper presents a browser extension called MailTrout, which incorporates machine learning within a usable security tool to assist users in detecting phishing emails. MailTrout demonstrated high levels of accuracy when detecting phishing emails and high levels of usability for end-users.",

author = "Paul Boyle and Shepherd, \{Lynsay A.\}",

note = "{\textcopyright} Boyle et al. Published by BCS Learning and Development Ltd. This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ Data availability statement: Not present.; 34rd British Human Computer Interaction Conference : Post-Pandemic HCI – Living digitally ; Conference date: 19-07-2021 Through 21-07-2021",

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Boyle, P & Shepherd, LA 2021, MailTrout: a machine learning browser extension for detecting phishing emails. in JA Nocera, H Petrie, G Sim, T Clemmensen & F Spyridonis (eds), 34th British Human Computer Interaction Conference 2021 proceedings: "Post-pandemic HCI – Living digitally". Electronic Workshops in Computing, BCS Learning & Development Ltd., pp. 104-115, 34rd British Human Computer Interaction Conference, London, United Kingdom, 19/07/21. https://doi.org/10.14236/ewic/HCI2021.10

MailTrout: a machine learning browser extension for detecting phishing emails. / Boyle, Paul; Shepherd, Lynsay A.
34th British Human Computer Interaction Conference 2021 proceedings: "Post-pandemic HCI – Living digitally". ed. / Jose Abdelnour Nocera; Helen Petrie; Gavin Sim; Torkil Clemmensen; Fotios Spyridonis. BCS Learning & Development Ltd., 2021. p. 104-115 (Electronic Workshops in Computing).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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AU - Shepherd, Lynsay A.

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AB - The onset of the COVID-19 pandemic has given rise to an increase in cyberattacks and cybercrime, particularly with respect to phishing attempts. Cybercrime associated with phishing emails can significantly impact victims, who may be subjected to monetary loss and identity theft. Existing anti-phishing tools do not always catch all phishing emails, leaving the user to decide the legitimacy of an email. The ability of machine learning technology to identify reoccurring patterns yet cope with overall changes complements the nature of anti-phishing techniques, as phishing attacks may vary in wording but often follow similar patterns. This paper presents a browser extension called MailTrout, which incorporates machine learning within a usable security tool to assist users in detecting phishing emails. MailTrout demonstrated high levels of accuracy when detecting phishing emails and high levels of usability for end-users.

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Boyle P, Shepherd LA. MailTrout: a machine learning browser extension for detecting phishing emails. In Nocera JA, Petrie H, Sim G, Clemmensen T, Spyridonis F, editors, 34th British Human Computer Interaction Conference 2021 proceedings: "Post-pandemic HCI – Living digitally". BCS Learning & Development Ltd. 2021. p. 104-115. (Electronic Workshops in Computing). Epub 2021 Jul 1. doi: 10.14236/ewic/HCI2021.10

MailTrout: a machine learning browser extension for detecting phishing emails

Abstract

Publication series

Conference

Keywords

UN SDGs

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