UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 9 Issue 11
November-2022
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR2211272


Registration ID:
504353

Page Number

c629-c632

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Title

A Survey On Identifying Fake Profiles Using Ann

Abstract

Fake identities or profiles plays major role in advanced persisted threats, like cyber espinoge, including theft secrets. These are also involved in malicious and dangerous activities. Currently social network plays a major role in order to perform day to day activities by the users. Due to excess use of social media networks different kinds of scammers are attracted to it. These scammers create different fake identities in order to carry out various scams. Due to presence of bots and fake profiles there are other dangers to personal data which are used for fraudulent purpose. Bots are type of program which access the data of users without users having information about them, it is also called web scrapping. To gain the access to private information these bots come in form of fake friend request or it can be hidden.In this project we are checking what is occurrence that the Facebook details are authentic or not by using Deep Learning-ANN. In order to perform these process we have extracted Facebook dataset from Github.Different libraries involved in this project. We have also sigmoid function to determine weights. Several parameters of any particular social media site which are very crucial in provided solutions are also consired.

Key Words

Fake Accounts (profiles) Identification , Artificial Neural Networks of deep learning , SVM and ANN classifications (machine learning) .

Cite This Article

"A Survey On Identifying Fake Profiles Using Ann", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.9, Issue 11, page no.c629-c632, November-2022, Available :http://www.jetir.org/papers/JETIR2211272.pdf

ISSN


2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"A Survey On Identifying Fake Profiles Using Ann", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.9, Issue 11, page no. ppc629-c632, November-2022, Available at : http://www.jetir.org/papers/JETIR2211272.pdf

Publication Details

Published Paper ID: JETIR2211272
Registration ID: 504353
Published In: Volume 9 | Issue 11 | Year November-2022
DOI (Digital Object Identifier): http://doi.one/10.1729/Journal.32111
Page No: c629-c632
Country: Hyderabad, Telangana, India .
Area: Science & Technology
ISSN Number: 2349-5162
Publisher: IJ Publication


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