Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study

<p dir="ltr">The advent of mobile technologies and social network applications has led to an increase in malicious scams and social engineering (SE) attacks which are causing loss of money and breaches of personal information. Understanding how SE attacks spread can provide useful in...

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Main Author: Bilikis Banire (14158833) (author)
Other Authors: Dena Al Thani (14149995) (author), Yin Yang (35103) (author)
Published: 2021
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author Bilikis Banire (14158833)
author2 Dena Al Thani (14149995)
Yin Yang (35103)
author2_role author
author
author_facet Bilikis Banire (14158833)
Dena Al Thani (14149995)
Yin Yang (35103)
author_role author
dc.creator.none.fl_str_mv Bilikis Banire (14158833)
Dena Al Thani (14149995)
Yin Yang (35103)
dc.date.none.fl_str_mv 2021-11-06T03:00:00Z
dc.identifier.none.fl_str_mv 10.3390/electronics10212709
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Investigating_the_Experience_of_Social_Engineering_Victims_Exploratory_and_User_Testing_Study/26946277
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Human-centred computing
social engineering
exploratory study
grounded theory
user testing study
dc.title.none.fl_str_mv Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">The advent of mobile technologies and social network applications has led to an increase in malicious scams and social engineering (SE) attacks which are causing loss of money and breaches of personal information. Understanding how SE attacks spread can provide useful information in curbing them. Artificial Intelligence (AI) has demonstrated efficacy in detecting SE attacks, but the acceptability of such a detection approach is yet to be investigated across users with different levels of SE awareness. This paper conducted two studies: (1) exploratory study where qualitative data were collected from 20 victims of SE attacks to inform the development of an AI-based tool for detecting fraudulent messages; and (2) a user testing study with 48 participants with different occupations to determine the detection tool acceptability. Overall, six major themes emerged from the victims’ actions “experiences: reasons for falling for attacks; attack methods; advice on preventing attacks; detection methods; attack context and victims”. The user testing study showed that the AI-based tool was accepted by all users irrespective of their occupation. The categories of users’ occupations can be attributed to the level of SE awareness. Information security awareness should not be limited to organizational levels but extend to social media platforms as public information.</p><h2>Other Information</h2><p dir="ltr">Published in: Electronics<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/electronics10212709" target="_blank">https://dx.doi.org/10.3390/electronics10212709</a></p>
eu_rights_str_mv openAccess
id Manara2_476363ff4e32151a179bce547044678e
identifier_str_mv 10.3390/electronics10212709
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/26946277
publishDate 2021
repository.mail.fl_str_mv
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rights_invalid_str_mv CC BY 4.0
spelling Investigating the Experience of Social Engineering Victims: Exploratory and User Testing StudyBilikis Banire (14158833)Dena Al Thani (14149995)Yin Yang (35103)Information and computing sciencesArtificial intelligenceCybersecurity and privacyHuman-centred computingsocial engineeringexploratory studygrounded theoryuser testing study<p dir="ltr">The advent of mobile technologies and social network applications has led to an increase in malicious scams and social engineering (SE) attacks which are causing loss of money and breaches of personal information. Understanding how SE attacks spread can provide useful information in curbing them. Artificial Intelligence (AI) has demonstrated efficacy in detecting SE attacks, but the acceptability of such a detection approach is yet to be investigated across users with different levels of SE awareness. This paper conducted two studies: (1) exploratory study where qualitative data were collected from 20 victims of SE attacks to inform the development of an AI-based tool for detecting fraudulent messages; and (2) a user testing study with 48 participants with different occupations to determine the detection tool acceptability. Overall, six major themes emerged from the victims’ actions “experiences: reasons for falling for attacks; attack methods; advice on preventing attacks; detection methods; attack context and victims”. The user testing study showed that the AI-based tool was accepted by all users irrespective of their occupation. The categories of users’ occupations can be attributed to the level of SE awareness. Information security awareness should not be limited to organizational levels but extend to social media platforms as public information.</p><h2>Other Information</h2><p dir="ltr">Published in: Electronics<br>License: <a href="https://creativecommons.org/licenses/by/4.0/" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.3390/electronics10212709" target="_blank">https://dx.doi.org/10.3390/electronics10212709</a></p>2021-11-06T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3390/electronics10212709https://figshare.com/articles/journal_contribution/Investigating_the_Experience_of_Social_Engineering_Victims_Exploratory_and_User_Testing_Study/26946277CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/269462772021-11-06T03:00:00Z
spellingShingle Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study
Bilikis Banire (14158833)
Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Human-centred computing
social engineering
exploratory study
grounded theory
user testing study
status_str publishedVersion
title Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study
title_full Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study
title_fullStr Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study
title_full_unstemmed Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study
title_short Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study
title_sort Investigating the Experience of Social Engineering Victims: Exploratory and User Testing Study
topic Information and computing sciences
Artificial intelligence
Cybersecurity and privacy
Human-centred computing
social engineering
exploratory study
grounded theory
user testing study