A Hybrid Scheme for Detecting Fake Accounts in Facebook
M. Smruthi1, N. Harini2

1M. Smruthi, Amrita School of Engineering, Amrita Viswa Vidyapeetham, Coimbatore (Tamil Nadu), India.
2Dr. N. Harini, Amrita School of Engineering, Amrita Viswa Vidyapeetham, Coimbatore (Tamil Nadu), India.
Manuscript received on 23 April 2019 | Revised Manuscript received on 02 May 2019 | Manuscript Published on 08 May 2019 | PP: 213-217 | Volume-7 Issue-5S3 February 2019 | Retrieval Number: E11400275S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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.
Keywords: Social Media, Facebook, Privacy, Social Network Analysis, Fake Profiles, Machine Learning, Skin Detection.
Scope of the Article: Social Networks