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Big Data Applications in Aadhar Card Fraud Detection

K. Ramya1 , A.Sumathi 2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-3 , Page no. 865-867, Mar-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i3.865867

Online published on Mar 31, 2019

Copyright © K. Ramya, A.Sumathi . 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: K. Ramya, A.Sumathi, “Big Data Applications in Aadhar Card Fraud Detection,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.3, pp.865-867, 2019.

MLA Style Citation: K. Ramya, A.Sumathi "Big Data Applications in Aadhar Card Fraud Detection." International Journal of Computer Sciences and Engineering 7.3 (2019): 865-867.

APA Style Citation: K. Ramya, A.Sumathi, (2019). Big Data Applications in Aadhar Card Fraud Detection. International Journal of Computer Sciences and Engineering, 7(3), 865-867.

BibTex Style Citation:
@article{Ramya_2019,
author = {K. Ramya, A.Sumathi},
title = {Big Data Applications in Aadhar Card Fraud Detection},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {3 2019},
volume = {7},
Issue = {3},
month = {3},
year = {2019},
issn = {2347-2693},
pages = {865-867},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3929},
doi = {https://doi.org/10.26438/ijcse/v7i3.865867}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i3.865867}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3929
TI - Big Data Applications in Aadhar Card Fraud Detection
T2 - International Journal of Computer Sciences and Engineering
AU - K. Ramya, A.Sumathi
PY - 2019
DA - 2019/03/31
PB - IJCSE, Indore, INDIA
SP - 865-867
IS - 3
VL - 7
SN - 2347-2693
ER -

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Abstract

Big Data is playing a very significant role to take any industry forward. In the fraud detection, automated fraud detection tries to collect all information to reduce in aadhar card frauds by doing analysis and data mining of Big Data. This paper investigates the benefits of Big Data technology and main methods of analysis that can be applied to the particular case of fraud detection in aadhar card. This paper hereby addresses aadhar card fraud detection via the use of data-mining techniques in classification of, Naive Bayesian (NB), c4.5, and Back Propagation (BP) analyze the customer data. In order to identify the patterns that can lead to frauds. Upon identify all sectors, adding a Aadhaar card include Name, Age, Date of Birth, Aadhaar Number ,Gender ,Photograph ,Residential Address, that are stored in data base according to biometric data are Fingerprints and Iris scan. Representing the Aadhaar number Details stored in the database in Fingerprints, Iris scan. Finally Aadhar card frauds are identified and detected using data mining algorithms.

Key-Words / Index Term

Big Data Analytics, Big Data Applications, and Aadhar card fraud detection, Classification Algorithm

References

[1] Mark A. Beyer and Douglas Laney. “The Importance of `Big Data`: A Definition”. Gartner, 2012. For book
[2] D. Fisher, R. DeLine, M. Czerwinski, and S. Drucker, “Interactions with big data analytics,” interactions, vol. 19, no. 3, pp. 50–59, May 2012. For journal
[3]Pang -Ning Tan, Vipin Kumar,Micheal Steinbach, “Introduction to data mining”, First Edition, 2012 For book
[4] D. Fisher, R. DeLine, M. Czerwinski, and S. Drucker, “Interactions with big data analytics,” interactions, vol. 19, no. 3, pp. 50–59, May 2012 For journal
[5] Jiawei Han, Micheline Kambar, Jian Pei, “Data Mining Concepts and Techniques” Elsevier Second Edition. For book
[6] B. Thuraisingham, L. Khan, M. Awad, and L. Wang, Design and Implementation of Data Mining Tools. Florida, USA: Auerbach Publication, 2009 For book