research-article

The uncertain case of credit card fraud detection

Authors:

Fabiana Fournier,

Inna SkarbovskyAuthors Info & Claims

DEBS '15: Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems

Pages 181 - 192

https://doi.org/10.1145/2675743.2771877

Published: 24 June 2015 Publication History

Abstract

Uncertainty is inherent in many real-time event-driven applications. Credit card fraud detection is a typical uncertain domain, where potential fraud incidents must be detected in real time and tagged before the transaction has been accepted or denied. We present extensions to the IBM Proactive Technology Online (PROTON) open source tool to cope with uncertainty. The inclusion of uncertainty aspects impacts all levels of the architecture and logic of an event processing engine. The extensions implemented in PROTON include the addition of new built-in attributes and functions, support for new types of operands, and support for event processing patterns to cope with all these. The new capabilities were implemented as building blocks and basic primitives in the complex event processing programmatic language. This enables implementation of event-driven applications possessing uncertainty aspects from different domains in a generic manner. A first application was devised in the domain of credit card fraud detection. Our preliminary results are encouraging, showing potential benefits that stem from incorporating uncertainty aspects to the domain of credit card fraud detection.

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Cited By

Rodrigues VPolicarpo Lda Silveira Dda Rosa Righi Rda Costa CBarbosa JAntunes RScorsatto RArcot T(2022)Fraud detection and prevention in e-commerceElectronic Commerce Research and Applications10.1016/j.elerap.2022.10120756:COnline publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1016/j.elerap.2022.101207
Jain APurwar AYadav D(2021)Credit Card Fraud Detection Using K-Means and Fuzzy C-MeansHandbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies10.4018/978-1-7998-6870-5.ch016(216-240)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-6870-5.ch016
Giatrakos NArtikis ADeligiannakis AGarofalakis M(2019)Uncertainty-Aware Event Analytics over Distributed SettingsProceedings of the 13th ACM International Conference on Distributed and Event-based Systems10.1145/3328905.3329763(175-186)Online publication date: 24-Jun-2019
https://dl.acm.org/doi/10.1145/3328905.3329763
Show More Cited By

Index Terms

The uncertain case of credit card fraud detection
1. Applied computing
  1. Electronic commerce
2. Computing methodologies
  1. Artificial intelligence
    1. Knowledge representation and reasoning
      1. Probabilistic reasoning
      2. Vagueness and fuzzy logic

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cover image ACM Conferences

DEBS '15: Proceedings of the 9th ACM International Conference on Distributed Event-Based Systems

June 2015

385 pages

ISBN:9781450332866

DOI:10.1145/2675743

General Chairs:
Frank Eliassen
University of Oslo, Norway
,
Roman Vitenberg
University of Oslo, Norway

Copyright © 2015 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 24 June 2015

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European Union

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DEBS '15

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DEBS '15: The 9th ACM International Conference on Distributed Event-Based Systems

June 29 - July 3, 2015

Oslo, Norway

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Overall Acceptance Rate 145 of 583 submissions, 25%

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Cited By

Rodrigues VPolicarpo Lda Silveira Dda Rosa Righi Rda Costa CBarbosa JAntunes RScorsatto RArcot T(2022)Fraud detection and prevention in e-commerceElectronic Commerce Research and Applications10.1016/j.elerap.2022.10120756:COnline publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1016/j.elerap.2022.101207
Jain APurwar AYadav D(2021)Credit Card Fraud Detection Using K-Means and Fuzzy C-MeansHandbook of Research on Innovations and Applications of AI, IoT, and Cognitive Technologies10.4018/978-1-7998-6870-5.ch016(216-240)Online publication date: 2021
https://doi.org/10.4018/978-1-7998-6870-5.ch016
Giatrakos NArtikis ADeligiannakis AGarofalakis M(2019)Uncertainty-Aware Event Analytics over Distributed SettingsProceedings of the 13th ACM International Conference on Distributed and Event-based Systems10.1145/3328905.3329763(175-186)Online publication date: 24-Jun-2019
https://dl.acm.org/doi/10.1145/3328905.3329763
Eshghi AKargari M(2019)Introducing a new method for the fusion of fraud evidence in banking transactions with regards to uncertaintyExpert Systems with Applications: An International Journal10.1016/j.eswa.2018.11.039121:C(382-392)Online publication date: 1-May-2019
https://dl.acm.org/doi/10.1016/j.eswa.2018.11.039
Kim JKim HKim H(2019)Fraud detection for job placement using hierarchical clusters-based deep neural networksApplied Intelligence10.1007/s10489-019-01419-249:8(2842-2861)Online publication date: 2-Aug-2019
https://dl.acm.org/doi/10.1007/s10489-019-01419-2
Khattri VSingh D(2018)Parameters of automated fraud detection techniques during online transactionsJournal of Financial Crime10.1108/JFC-03-2017-002425:3(702-720)Online publication date: 2-Jul-2018
https://doi.org/10.1108/JFC-03-2017-0024
Correia IArtikis AKatzouris NBaber CMorar NSkarbovsky IFournier FPaliouras G(2017)Demonstration of a Prototype for Credit Card Fraud ManagementProceedings of the 11th ACM International Conference on Distributed and Event-based Systems10.1145/3093742.3095096(335-338)Online publication date: 8-Jun-2017
https://dl.acm.org/doi/10.1145/3093742.3095096
Yadav Pul Hassan UHasan SCurry E(2017)The Event CrowdProceedings of the 11th ACM International Conference on Distributed and Event-based Systems10.1145/3093742.3093922(44-53)Online publication date: 8-Jun-2017
https://dl.acm.org/doi/10.1145/3093742.3093922
Artikis AKatzouris NCorreia IBaber CMorar NSkarbovsky IFournier FPaliouras G(2017)A Prototype for Credit Card Fraud ManagementProceedings of the 11th ACM International Conference on Distributed and Event-based Systems10.1145/3093742.3093912(249-260)Online publication date: 8-Jun-2017
https://dl.acm.org/doi/10.1145/3093742.3093912
Petersen ETo MMaag S(2016)An online learning based approach for CEP rule generation2016 8th IEEE Latin-American Conference on Communications (LATINCOM)10.1109/LATINCOM.2016.7811563(1-6)Online publication date: Nov-2016
https://doi.org/10.1109/LATINCOM.2016.7811563

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