Explainable AI With Imbalanced Learning Strategies for Blockchain Transaction Fraud Detection

ABSTRACT Blockchain networks now support billions of dollars in daily transactions, making reliable and transparent fraud detection essential for maintaining user trust and financial stability. Yet, real‐world blockchain datasets are extremely imbalanced, with fraudulent activity representing less t...

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Egile Nagusiak:	Ahmed Abbas Jasim Al‐Hchaimi, M. A. Khalifa, Walid El‐Shafai
Formatua:	Artigo
Hizkuntza:	Inglês
Argitaratua:	Wiley 2026-01-01
Saila:	Engineering Reports
Gaiak:	ADASYN Blockchain analytics explainable artificial intelligence fraud detection imbalanced learning LightGBM
Sarrera elektronikoa:	https://doi.org/10.1002/eng2.70545
Etiketak:	Etiketa erantsi Etiketarik gabe, Izan zaitez lehena erregistro honi etiketa jartzen!