Avaliando Modelos de Graph Neural Networks para Detecção de Usuários Fraudulentos em e-Commerce

• Larissa de Andrade Silva UFAM http://orcid.org/0000-0001-9489-1729
• Eduardo L. Feitosa UFAM https://orcid.org/0000-0001-6401-3992

DOI: https://doi.org/10.5753/sbseg_estendido.2021.17361

Resumo

Modelos baseados em grafos, Graph Neural Networks ou (GNN), vêm sendo empregados na detecção de fraudes no comércio eletrônico com resultados promissores. Neste trabalho foram avaliados modelos que utilizam classificação sobre os nós, baseados em informações da vizinhança, e o reconhecimento de comunidade, utilizando datasets reais. Os resultados demonstram que, embora promissores (acurácia variando de 50% a 86%), ainda é preciso estudar e investigá-los melhor para que possam, no futuro, atuarem em soluções anti-fraude.

Palavras-chave: gnn, comércio eletrônico, fraude

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