IDENTIFING OF PHONY ACCOUNTS ACROSS ONLINE SOCIAL NETWORKS BY USING SEMANTIC NETWORK

Abstract

Considering the current state of
affairs, it's clear that most people's attention is
focused on online social networks. Everyone
from kids to adults spends a lot of time on these
sites, either socializing or doing work. In today's
world, however, these platforms are plagued by
a rising number of phony identities that exploit
security flaws in order to steal from the sites or
to steal from other users who are themselves
committing cybercrimes. However, with this
rise in online networking comes a rise in issues
such as profile forgery and online
impersonation. When phony users upload
information online, it fills up user feeds with
information they don't need. Twenty percent to
forty percent of profiles on social networking
sites like Facebook have been shown to be
fictitious. Thus, a framework-based solution has
emerged for identifying phony accounts in
social media.