DriftShield: Autonomous Fraud Detection via Actor-Critic Reinforcement Learning With Dynamic Feature Reweighting
Financial fraud detection systems confront the persistent challenge of concept drift, where fraudulent patterns evolve continuously to evade detection mechanisms. Traditional rule-based methods and static machine learning models require frequent manual updates, failing to autonomously adapt to emerg...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
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| Series: | IEEE Open Journal of the Computer Society |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/11072929/ |
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