  Social networks play a significant role in today's world. The importance of
social networks, for example Facebook or Twitter, are undeniable. However, they
also have many issues. One of which is the need for a defense mechanism against
fake accounts. It is obviously not a trivial task to separate fake accounts
from authentic ones. In this paper, we propose a ranking scheme, comprising of
both graph based and feature based approaches to aid the detection of fake
Facebook profiles. Utilizing Support Vector Machine (SVM) \cite{cortes1995} and
SybilWalk \cite{JWZ17}, the model achieved high accuracy over the set of ten
thousands Vietnamese Facebook accounts.
