A conceptual model to predict social engineering victims

Samar Muslah Albladi; George R.S. Weir

doi:10.1109/ICGS3.2019.8688352

A conceptual model to predict social engineering victims

Samar Muslah Albladi, George R.S. Weir

Computer And Information Sciences

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

1 Citation (Scopus)

28 Downloads (Pure)

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.

Original language	English
Title of host publication	2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3)
Place of Publication	Piscataway, N.J.
Number of pages	1
ISBN (Electronic)	9781538670019
DOIs	https://doi.org/10.1109/ICGS3.2019.8688352
Publication status	Published - 10 Apr 2019
Event	12th International Conference on Global Security, Safety and Sustainability, ICGS3 2019 - London, United Kingdom Duration: 16 Jan 2019 → 18 Jan 2019

Conference

Conference	12th International Conference on Global Security, Safety and Sustainability, ICGS3 2019
Country	United Kingdom
City	London
Period	16/01/19 → 18/01/19

Keywords

social engineering
online user threat
social networks

Access to Document

10.1109/ICGS3.2019.8688352

Albladi-Weir-ICGS3-2019-A-conceptual-model-to-predict-social-engineeringAccepted author manuscript, 312 KB

Link to publication in Scopus

Cite this

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title = "A conceptual model to predict social engineering victims",

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.",

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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, 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

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