Identifying Fake Profile in Online Social Network: An Overview and Survey

Abstract

Online Social Networks (OSNs) presently engage the majority of people, from a child to an adult and even old age people as they spend a good amount of time on these platforms exchanging their information and creating interaction with other people of the world. On one hand, these social networks provide the advantage of direct connectivity between people, information sharing, ways to create a large audience, etc. on the other hand people also misuse them in many ways. Social networking sites are suffering from people who own bulk of fake accounts to take advantage of vulnerabilities for their immoral benefits such as intriguing targeted accounts to click on malicious links or to attempt any other cybercrimes. These actions motivate researchers to develop a system that can detect fake accounts on these OSNs. Several attempts have been made by the researchers to detect the accounts on social networking sites as fake or real, relying on account’s features (user-based, graph-based, content-based, time-based) and various classification algorithms. In this paper, we provide an overview of various studies done in this direction and a survey of all the techniques already used and can be used in the future.