Nowadays, online social media has become an inseparable part of human life,
also this phenomenon is being used by individuals to send messages and share
files via videos and images. Twitter, Instagram, and Facebook are well-known
samples of these networks. One of the main challenges of privacy for users in
these networks is anomalies in security. Anomalies in online social networks
can be attributed to illegal behavior, such deviance is done by malicious
people like account forgers, online fraudsters, etc. This paper proposed a new
method to identify fake user accounts by calculating the similarity measures
among users, applying the Generative Adversarial Network (GAN) algorithm over
the Twitter dataset. The results of the proposed method showed, accuracy was
able to reach 98.1% for classifying and detecting fake user accounts