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.
| Language | English |
|---|---|
| Title of host publication | 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3) |
| Place of Publication | Piscataway, N.J. |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Number of pages | 1 |
| ISBN (Electronic) | 9781538670019 |
| DOIs | |
| 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
Cite this
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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 proceeding › Conference contribution book
TY - GEN
T1 - A conceptual model to predict social engineering victims
AU - Muslah Albladi, Samar
AU - Weir, George R.S.
PY - 2019/4/10
Y1 - 2019/4/10
N2 - 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.
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.
KW - social engineering
KW - online user threat
KW - social networks
UR - http://www.scopus.com/inward/record.url?scp=85065026659&partnerID=8YFLogxK
U2 - 10.1109/ICGS3.2019.8688352
DO - 10.1109/ICGS3.2019.8688352
M3 - Conference contribution book
BT - 2019 IEEE 12th International Conference on Global Security, Safety and Sustainability (ICGS3)
PB - Institute of Electrical and Electronics Engineers Inc.
CY - Piscataway, N.J.
ER -