Publication Type:

Journal Article

Source:

International Journal of Recent Technology and Engineering (IJRTE), Volume 7, Issue 5S3 (2019)

URL:

https://www.ijrte.org/wp-content/uploads/papers/v7i5s3/E11400275S19.pdf

Keywords:

Facebook, Fake Profiles, Machine learning, Privacy, Skin Detection., Social media, Social Network Analysis

Abstract:

A social networking service serves as a platform to
build social networks or social relations among people who,
share interests, activities, backgrounds, or real life connections.
A social network service is generally offered to participants who
registers to this site with their unique representation (often a
profile) and one’s social links. Most social network services are
web-based and provide means for users to interact over the
Internet. Nevertheless these sites are also constantly preyed by
hackers raising various problems related to threats and attacks
such as disclosure of information, identity thefts etc. One of the
most common ways of performing a large-scale data harvesting
attack is the use of fake profiles, where malicious users present
themselves in profiles impersonating fictitious or real persons.
An attempt has been made in this work to use a hybrid model
based on machine learning and skin detection algorithms to
detect the existence of fake accounts. The experimentation
process clearly brought out the strength of the proposed scheme
in terms of detecting fake accounts with high accuracy.

Cite this Research Publication

M. Smruthi and Harini, N., “A hybrid scheme for detecting fake accounts in facebook”, International Journal of Recent Technology and Engineering (IJRTE), vol. 7, no. 5S3, 2019.