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Automatic Detection of Fake Profiles in Online Social Networks

R.V. Kotawadekar1 , A.S. Kamble2 , S.A. Surve3

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-7 , Page no. 40-45, Jul-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i7.4045

Online published on Jul 31, 2019

Copyright © R.V. Kotawadekar, A.S. Kamble, S.A. Surve . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: R.V. Kotawadekar, A.S. Kamble, S.A. Surve, “Automatic Detection of Fake Profiles in Online Social Networks,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.7, pp.40-45, 2019.

MLA Style Citation: R.V. Kotawadekar, A.S. Kamble, S.A. Surve "Automatic Detection of Fake Profiles in Online Social Networks." International Journal of Computer Sciences and Engineering 7.7 (2019): 40-45.

APA Style Citation: R.V. Kotawadekar, A.S. Kamble, S.A. Surve, (2019). Automatic Detection of Fake Profiles in Online Social Networks. International Journal of Computer Sciences and Engineering, 7(7), 40-45.

BibTex Style Citation:
@article{Kotawadekar_2019,
author = {R.V. Kotawadekar, A.S. Kamble, S.A. Surve},
title = {Automatic Detection of Fake Profiles in Online Social Networks},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {7 2019},
volume = {7},
Issue = {7},
month = {7},
year = {2019},
issn = {2347-2693},
pages = {40-45},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4717},
doi = {https://doi.org/10.26438/ijcse/v7i7.4045}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i7.4045}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4717
TI - Automatic Detection of Fake Profiles in Online Social Networks
T2 - International Journal of Computer Sciences and Engineering
AU - R.V. Kotawadekar, A.S. Kamble, S.A. Surve
PY - 2019
DA - 2019/07/31
PB - IJCSE, Indore, INDIA
SP - 40-45
IS - 7
VL - 7
SN - 2347-2693
ER -

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Abstract

In the present generation, the social life of everyone has become associated with the online social networks. These sites have made a drastic change in the way we pursue our social life. Making friends and keeping in contact with them and their updates has become easier. But with their rapid growth, many problems like fake profiles, online impersonation have also grown. There are no feasible solution exist to control these problems. In this project, we came up with a framework with which automatic detection of fake profiles is possible and is efficient. This framework uses classification techniques like Support Vector Machine, Naive Bayes and Decision trees to classify the profiles into fake or genuine classes. As, this is an automatic detection method, it can be applied easily by online social networks which has millions of profile whose profiles cannot be examined manually.

Key-Words / Index Term

Threats, Facebook Immune System, Classification, Training Datasets, Profile Attributes

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