A SURVEY ON FAKE PROFILE IDENTIFICATION USING MACHINE LEARNING TECHNIQUES









Abstract

In this survey paper, we have gathered nearly 30 papers to helps us in the fake profile identification. The social network, which is such a vital part of our lives, is plagued by online impersonation and bogus accounts. According to Facebook's 'Community Standards Enforcement Report,' over 583 million fraudulent accounts were shut down in the first quarter of 2018, with 3-4 percent of active accounts still being fake. We present a model for determining whether an account is fake or authentic in this study. This model uses the Support Vector Machine as a classification technique and can analyse a large dataset of accounts at once, eliminating the requirement for each account to be individually evaluated. Our community of concern is Fake Accounts, and our predicament might be regarded as a categorization or clustering issue.


Modules


Algorithms


Software And Hardware