  Homograph attack is a way that attackers deceive victims about which website
domain name they are communicating with by exploiting the fact that many
characters look alike. The attack becomes serious and is raising broad
attention when recently many brand domains have been attacked such as Apple
Inc., Adobe Inc., Lloyds Bank, etc. We first design a survey of human
demographics, brand familiarity, and security backgrounds and apply it to 2,067
participants. We build a regression model to study which factors affect
participants' ability in recognizing homograph domains. We find that for
different levels of visual similarity, the participants exhibit different
abilities. 13.95% of participants can recognize non-homographs while 16.60% of
participants can recognize homographs whose the visual similarity with the
target brand domains is under 99.9%; but when the similarity increases to
99.9%, the number of participants who can recognize homographs significantly
drops down to only 0.19%; and for the homographs with 100% of visual
similarity, there is no way for the participants to recognize. We also find
that female participants tend to recognize homographs better the male but male
participants tend to able to recognize non-homographs better than females.
Security knowledge is a significant factor affecting both homographs and
non-homographs; surprisingly, people who have strong security knowledge tend to
be able to recognize homographs but not non-homographs. Furthermore, people who
work or are educated in computer science or computer engineering do not appear
as a factor affecting the ability in recognizing homographs; however,
interestingly, right after they are explained about the homograph attack,
people who work or are educated in computer science or computer engineering are
the ones who can capture the situation the most quickly.

Cryptography and Security