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View all- 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
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
Javier Cabezas, Alberto Fernandez-Isabel, Rubén R. Fernández, César González-Fernández, Adrián Alonso, Isaac Martín de DiegoAuthors Info & ClaimsPages 67 - 71
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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- Bio-Inspired Agent-Based Architecture for Fraud Detection
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August 2020
120 pages
ISBN:9781450375467
DOI:10.1145/3416028
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- Southwest Jiaotong University
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Publication History
Published: 21 September 2020
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- Refereed limited
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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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View all- 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
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