An Approach to Identify Fake Profile in Online Social Networks Using Network Graph Analysis

Abstract

In the present generation, Online Social Networks have become an essential part of internet users to perform different activities like sharing different information in the form of personal information, videos, pictures, discussions on different topics, product reviews, research and e-business. The popularity of these platforms such as Facebook and Twitter etc. attracted cyber criminals to violate and abuse the network services for illicit gain. These cyber criminals includes the fraudsters, imposters, scammers social bots, phishers and spammers etc. These attackers exploit the platform for personal gain particularly by using fake profiles. Fake profiles can be used for a variety of purpose but the primary purpose of such profiles include fake followers, spread mislead content and scamming. The online social network’s overall reputation is affected by fake profiles. A spam account is a type of fake account that can be human generated or bot generated. The primary purpose of spammers is to distribute misleading information, malicious content, posting malicious users and send spontaneous messages to a large group of audience. A lot of existing research is available to detect fake profiles in online social networks but there is no feasible method available to overcome this problem. A model is much needed that can identify fake profiles in online social network. In this thesis, author performed a systematic literature review for fake profile detection in online social network.