1. Male, late with your credit card payment, and like to speed? You will be phished. Markus Jakobsson

2. Why are we asked if we smoke?

3. Experiment: setup Recruit 500 subjects from Mechanical Turk using survey “Have you lost money to online fraud?” (1 cent) victims non-victims

4. Experiment: setup Recruit 500 subjects from Mechanical Turk using survey “Have you lost money to online fraud?” (1 cent) Invite all “yes” (~150) and same number of “no”. victims non-victims

5. Experiment: setup victims non-victims

6. Experiment: setup Recruit 500 subjects from Mechanical Turk using survey “Have you lost money to online fraud?” (1 cent) Invite all “yes” (~150) and same number of “no”. Final numbers: 101 “yes”, 100 “no” victims non-victims

7. Experiment: survey (demographics)

8. Experiment: survey (physical risks)

9. Experiment: survey (financial risks)

10. Experiment: survey (information risks)

11. Some results Same pwd many site Download free softw. Using public wifi Click link email Resp. unsolic. off. .23 .23 Invest real est. Invest stocks Invest bonds Not paying cc bal. Being late cc pay Save <5% retire Make inv. rec fr. .23 .27 .29 .27 .21 .28 .24 .23 .19 .27 .23 .33 .26 .32 .24 .30 .25 .26 .24 .27 .28 .25 .27 .30 Correlations significant on 0.05 level

12. Some results - hard facts • Weaker, but still there - need more variables! • Example (with 0.01 significance) • “Other fraud” ~ “Not paying cc balance” (0.19) • ~ “Save less 5% retirement” (0.17) • Notable correlations between types of fraud • Some negative correlations! • Machine Learning efforts under way Thanks to Nathan Good for helpful discussions