From: User characteristics that influence judgment of social engineering attacks in social networks
Expert number | Age | Gender | Education | Expertise (years) |
---|---|---|---|---|
Expert 1 | 35–44 | Male | Ph.D. | Over 15 |
Expert 2 | 35–44 | Male | Ph.D. | 11–15 |
Expert 3 | 35–44 | Female | Ph.D. | Over 15 |
Expert 4 | 35–44 | Female | Ph.D. | 11–15 |
Expert 5 | 35–44 | Female | Master | 11–15 |
Expert 6 | 25–34 | Male | Master | 6–10 |
Expert 7 | 35–44 | Female | Master | 6–10 |
Expert 8 | 35–44 | Female | Master | 6–10 |
Expert 9 | 25–34 | Male | Master | 1–5 |
Expert 10 | 25–34 | Male | Bachelor | 1–5 |
Expert 11 | 25–34 | Male | Bachelor | 1–5 |