research-article

Bio-Inspired Agent-Based Architecture for Fraud Detection

Authors:

Javier Cabezas,

Alberto Fernandez-Isabel,

Rubén R. Fernández,

César González-Fernández,

Adrián Alonso,

Isaac Martín de DiegoAuthors Info & Claims

IMMS '20: Proceedings of the 3rd International Conference on Information Management and Management Science

Pages 67 - 71

https://doi.org/10.1145/3416028.3416039

Published: 21 September 2020 Publication History

Abstract

The information accessible on the Internet has been drastically increased over the last years. This information is not always produced by trusted sources. This fact leads to the emergence of fraudulent websites containing unappropriated information or having malicious intentions. The analysis of this large amount of information to detect possible fraud situations tends to be a very demanding task for human experts. Thus, it becomes a key issue to automatise these operations. This paper presents a Multi-Agent System (MAS) model and its implementation focused on automatically detecting fraudulent websites. The INGENIAS methodology and the MESA framework have been selected for this purpose. The system consists of a bio-inspired agent-based architecture based on insect colonies. Several basic agents carry out simple and distributed operations, while there is just one agent which aggregates the individual outcomes to obtain the final result. Some websites have been selected to illustrate the viability of the proposal.

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Cited By

Moreno RFernández-Isabel AAceña VMartín de Diego IMoguerza J(2024)Tourist services management through clients scoring using a bio-inspired agent architectureComputer Science and Information Systems10.2298/CSIS231120034M21:4(1243-1268)Online publication date: 2024
https://doi.org/10.2298/CSIS231120034M
Liang XLuo LHu SLi Y(2022)Mapping the knowledge frontiers and evolution of decision making based on agent-based modelingKnowledge-Based Systems10.1016/j.knosys.2022.108982250:COnline publication date: 17-Aug-2022
https://dl.acm.org/doi/10.1016/j.knosys.2022.108982

Index Terms

Bio-Inspired Agent-Based Architecture for Fraud Detection
1. Computing methodologies
  1. Modeling and simulation
    1. Simulation types and techniques
      1. Agent / discrete models

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cover image ACM Other conferences

IMMS '20: Proceedings of the 3rd International Conference on Information Management and Management Science

August 2020

120 pages

ISBN:9781450375467

DOI:10.1145/3416028

Copyright © 2020 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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Southwest Jiaotong University

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 21 September 2020

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Ministerio de Economía y Competitividad

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IMMS 2020

IMMS 2020: 2020 3rd International Conference on Information Management and Management Science

August 7 - 9, 2020

London, United Kingdom

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Cited By

Moreno RFernández-Isabel AAceña VMartín de Diego IMoguerza J(2024)Tourist services management through clients scoring using a bio-inspired agent architectureComputer Science and Information Systems10.2298/CSIS231120034M21:4(1243-1268)Online publication date: 2024
https://doi.org/10.2298/CSIS231120034M
Liang XLuo LHu SLi Y(2022)Mapping the knowledge frontiers and evolution of decision making based on agent-based modelingKnowledge-Based Systems10.1016/j.knosys.2022.108982250:COnline publication date: 17-Aug-2022
https://dl.acm.org/doi/10.1016/j.knosys.2022.108982

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