Fake Profile Detection in Online Social Networks Using Machine Learning Models

A new era of networking has emerged due to the easy access of social networks. People can share a lot of information using online social networks. Some of the widely used social networks are Twitter, Facebook, Google+, Instagram, Pinterest and LinkedIn. The majority of social network users are ignorant of the security threats that OSNs pose. There are several issues with modern online social networks, such as fraudulent profiles and online impersonation. False profiles spread inaccurate information about a certain individual or make fraudulent attempts with bad intentions. Fake profiles can be identified using machine learning techniques. Various machine learning models, such as Support Vector Machine, Decision Tree, Neural Networks, Random Forest, Naive Bayes, Logistic Regression, and K-nearest Neighbor can be employed for the detection of fake profiles. The different machine learning techniques for identifying fake profiles are compared in this paper.