short-paper

Application of cluster analysis for the assessment of the share of fraud victims among bank card holders

Authors:

S. S. Alkhasov,

A. A. TselykhAuthors Info & Claims

SIN '15: Proceedings of the 8th International Conference on Security of Information and Networks

Pages 103 - 106

https://doi.org/10.1145/2799979.2800033

Published: 08 September 2015 Publication History

Abstract

In this paper, we present a method for the assessment of the share of cardholders most prone to various types of bank fraud (i.e. fishing, vishing, skimming). For this purpose, a forecasting information system has been designed. It is based on a clustering module used for output of a certain set of cluster indices that depend on the percentage of aggrieved clients in the training sample. The k-means method is used for clustering. The initial coordinates of centroids are defined using advanced k-means++ algorithm.

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Cited By

Han WZhang SGao HBu D(2024)Clustering on hierarchical heterogeneous data with prior pairwise relationshipsBMC Bioinformatics10.1186/s12859-024-05652-625:1Online publication date: 23-Jan-2024
https://doi.org/10.1186/s12859-024-05652-6
Manzali YBarry KFlouchi RBalouki YElfar M(2024)An innovative clustering approach utilizing frequent item setsMultimedia Tools and Applications10.1007/s11042-024-18913-6Online publication date: 26-Apr-2024
https://doi.org/10.1007/s11042-024-18913-6
Chen HAi HYang ZYang WYe ZDong D(2020)An Improved XGBoost Model Based on Spark for Credit Card Fraud Prediction2020 IEEE 5th International Symposium on Smart and Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS)10.1109/IDAACS-SWS50031.2020.9297058(1-6)Online publication date: 17-Sep-2020
https://doi.org/10.1109/IDAACS-SWS50031.2020.9297058
Show More Cited By

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Application of cluster analysis for the assessment of the share of fraud victims among bank card holders

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Published In

cover image ACM Other conferences

SIN '15: Proceedings of the 8th International Conference on Security of Information and Networks

September 2015

350 pages

ISBN:9781450334532

DOI:10.1145/2799979

Conference Chairs:
Oleg Makarevich
Southern Federal University, Russia
,
Ron Poet
University of Glasgow, UK
,
Atilla Elçi
Aksaray University, Turkey
,
Manoj Singh Gaur
Malaviya National Institute of Technology, India
,
Mehmet Orgun
Macquarie University, Australia
,
Program Chairs:
Ludmila Babenko
Southern Federal University, Russia
,
Sadek Ferdous
University of Glasgow, UK
,
Anthony T. S. Ho
University of Surrey, UK
,
Vijay Laxmi
Malaviya National Institute of Technology, India
,
Josef Pieprzyk
Queensland University of Technology, Australia

Copyright © 2015 ACM.

Publication rights licensed to ACM. ACM acknowledges that this contribution was authored or co-authored by an employee, contractor or affiliate of a national government. As such, the Government retains a nonexclusive, royalty-free right to publish or reproduce this article, or to allow others to do so, for Government purposes only.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 September 2015

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Short-paper

Funding Sources

Russian Foundation for Basic Research

Conference

SIN '15

SIN '15: The 8th International Conference on Security of Information and Networks

September 8 - 10, 2015

Sochi, Russia

Acceptance Rates

SIN '15 Paper Acceptance Rate 34 of 92 submissions, 37%;

Overall Acceptance Rate 102 of 289 submissions, 35%

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Cited By

Han WZhang SGao HBu D(2024)Clustering on hierarchical heterogeneous data with prior pairwise relationshipsBMC Bioinformatics10.1186/s12859-024-05652-625:1Online publication date: 23-Jan-2024
https://doi.org/10.1186/s12859-024-05652-6
Manzali YBarry KFlouchi RBalouki YElfar M(2024)An innovative clustering approach utilizing frequent item setsMultimedia Tools and Applications10.1007/s11042-024-18913-6Online publication date: 26-Apr-2024
https://doi.org/10.1007/s11042-024-18913-6
Chen HAi HYang ZYang WYe ZDong D(2020)An Improved XGBoost Model Based on Spark for Credit Card Fraud Prediction2020 IEEE 5th International Symposium on Smart and Wireless Systems within the Conferences on Intelligent Data Acquisition and Advanced Computing Systems (IDAACS-SWS)10.1109/IDAACS-SWS50031.2020.9297058(1-6)Online publication date: 17-Sep-2020
https://doi.org/10.1109/IDAACS-SWS50031.2020.9297058
Ghosal ANandy ADas AGoswami SPanday M(2019)A Short Review on Different Clustering Techniques and Their ApplicationsEmerging Technology in Modelling and Graphics10.1007/978-981-13-7403-6_9(69-83)Online publication date: 17-Jul-2019
https://doi.org/10.1007/978-981-13-7403-6_9

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