In this paper, we propose a novel framework, GIANTESS, to enhance the detection of stealthy fraud transactions by leveraging unlabeled suspicious records.
Dec 5, 2024 · In this work, we propose xFraud, an explainable fraud transaction prediction framework which is mainly composed of a detector and an explainer.
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Aug 13, 2024 · 1) It slashes false positives. UML doesn't need labeled data; it analyzes large sets of unlabeled data to find hidden patterns and spot new threats.
Oct 30, 2024 · Fraud analytics integrates advanced data analysis with forensic techniques to detect, resist, and prevent dishonest behaviors.
Apr 10, 2024 · This article examines advanced technologies such as data mining, machine learning, biometric authentication, and blockchain through a comprehensive review of ...
Feb 22, 2024 · This paper introduces a novel method for credit card fraud detection, the Causal Temporal Graph Neural Network (CaT-GNN), which leverages causal ...
This guide provides a step-by-step approach to building a financial fraud detection solution, enhancing accuracy and speed in identifying and preventing ...
Aug 7, 2024 · This technique can enhance fraud detection by leveraging vast amounts of unannotated transaction data. Integration with Other Security ...
Jun 16, 2024 · Semi-supervised learning can enhance the accuracy of fraud detection by incorporating unlabeled data to refine the model's understanding of ...
Aug 4, 2023 · This paper presents a holistic applied data science approach to fraud detection in the Bitcoin network with two original contributions.