A conceptual model to predict social engineering victims

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

Abstract

Social engineering (SE) attacks are a serious threat to online users and might subject people to different kinds of harm. Despite increased concern with this risk, there has been little research activity focused upon social engineering in the potentially rich hunting ground of social networks. The number of victims of social engineering attacks will be decreased if the users' detection ability has improved. Yet, this improvement of the user's detection behaviour can't be occurred without investigating the users' weakness points. The present study develops a conceptual model to test the factors that influence social networks users' judgment of social engineering-based attacks in order to identify the weakest points of users' detection behaviour which also help to predict vulnerable individuals.

LanguageEnglish
Title of host publication2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3)
Place of PublicationPiscataway, N.J.
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages1
ISBN (Electronic)9781538670019
DOIs
Publication statusPublished - 10 Apr 2019
Event12th International Conference on Global Security, Safety and Sustainability, ICGS3 2019 - London, United Kingdom
Duration: 16 Jan 201918 Jan 2019

Conference

Conference12th International Conference on Global Security, Safety and Sustainability, ICGS3 2019
CountryUnited Kingdom
CityLondon
Period16/01/1918/01/19

Keywords

  • social engineering
  • online user threat
  • social networks

Cite this

Muslah Albladi, S., & Weir, G. R. S. (2019). A conceptual model to predict social engineering victims. In 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3) [8688352] Piscataway, N.J.: Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICGS3.2019.8688352
Muslah Albladi, Samar ; Weir, George R.S. / A conceptual model to predict social engineering victims. 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3). Piscataway, N.J. : Institute of Electrical and Electronics Engineers Inc., 2019.
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Muslah Albladi, S & Weir, GRS 2019, A conceptual model to predict social engineering victims. in 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3)., 8688352, Institute of Electrical and Electronics Engineers Inc., Piscataway, N.J., 12th International Conference on Global Security, Safety and Sustainability, ICGS3 2019, London, United Kingdom, 16/01/19. https://doi.org/10.1109/ICGS3.2019.8688352

A conceptual model to predict social engineering victims. / Muslah Albladi, Samar; Weir, George R.S.

2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3). Piscataway, N.J. : Institute of Electrical and Electronics Engineers Inc., 2019. 8688352.

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

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T1 - A conceptual model to predict social engineering victims

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AB - Social engineering (SE) attacks are a serious threat to online users and might subject people to different kinds of harm. Despite increased concern with this risk, there has been little research activity focused upon social engineering in the potentially rich hunting ground of social networks. The number of victims of social engineering attacks will be decreased if the users' detection ability has improved. Yet, this improvement of the user's detection behaviour can't be occurred without investigating the users' weakness points. The present study develops a conceptual model to test the factors that influence social networks users' judgment of social engineering-based attacks in order to identify the weakest points of users' detection behaviour which also help to predict vulnerable individuals.

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Muslah Albladi S, Weir GRS. A conceptual model to predict social engineering victims. In 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3). Piscataway, N.J.: Institute of Electrical and Electronics Engineers Inc. 2019. 8688352 https://doi.org/10.1109/ICGS3.2019.8688352