Unfortunately this Infographic called “How to Spot a Liar” would not be very useful in online scams like 419 Fraud. The references hint that technology may have been left out of focus; do people really lie more often on the telephone than with email or IM?
Spoiler alert, this is their list:
- Listen to how they say what they say
- Watch their body language
- Detect irregular emotional patterns
- Recognize awkward interactions
- Study subtle facial expressions
- Understand eye movements
First, although this Infographic says it will help you spot a liar, the list is nearly impossible to use with online fraud as I pointed out above. That seems to me a strange oversight. That is why I titled this post how to detect fraud in-person. It still seems useful that regard.
Second, however, it appears to fail to bridge cultural differences, the very foundation of 419 fraud — attackers can use differences to exploit victims through social engineering. If you expect an African to have funny body language because you don’t know much about Africa or Africans, then you will be unable to use their #2 recommendation. In fact, you might be more likely to be a victim because you think #2 is a good test but you also think you have to disable it because you are more convinced that Africans have funny body language.
Third, the list gives examples from a baseline that may not fit your situation. It comes from a particular view which may not be suited to every environment. It suggests to watch for people who repeat what you say, for example. Yet I have found this to be common in some rural communities. As an outsider from the city I may find it unusual but I am not about to suggest that rural inhabitants should be trusted less because they behave differently from me. I see a tendency in the Infographic to assume that time in a zone is the same thing as time.
Overall it’s a good presentation on specific fraud vectors and specific detection methods. It would be easy to add the the above points to the Infographic and make it more flexible, as we have described in our paper and presentations.
Attacks by scammers appear to make sophisticated use of language ideology to abuse trust relationships. Language that indexes Africans allows perceived â€˜authenticityâ€™ to be constructed in a way that breaks down a victimsâ€™ defenses â€” a variety of linguistic devices are used as attack tools.
In the meantime it serves as a good illustration of how a fraud detection system could backfire or fail a simple change of environment.