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

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submitted on 2024-09-05, 10:38 and posted on 2024-09-08, 05:41 authored by Bilikis Banire, Dena Al Thani, Yin Yang

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.

Other Information

Published in: Electronics
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.3390/electronics10212709

Funding

Qatar National Research Fund (NPRP10-0208-170408), Detecting Fraudulent Messages with Strong Privacy Protection.

History

Language

  • English

Publisher

MDPI

Publication Year

  • 2021

License statement

This Item is licensed under the Creative Commons Attribution 4.0 International License.

Institution affiliated with

  • Hamad Bin Khalifa University
  • College of Science and Engineering - HBKU

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    College of Science and Engineering - HBKU

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