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Research on Credit Card Fraud Detection System Based on Federated Learning

Ya Wen

Abstract


With the rapid development of the mobile Internet, financial technology, especially artificial intelligence and blockchain technology,
has profoundly changed our consumer behavior and the development model of the traditional financial industry. However, the accompanying risks are also being transmitted with unprecedented speed and complexity. Credit card fraud, as an important form of financial fraud, has
caused huge economic losses and a crisis of trust for both financial institutions and consumers. Therefore, the establishment of an efficient and
secure credit card fraud detection system has become an inevitable requirement for the continuous development of financial technology in the
new era. The purpose of this paper is to study and develop a credit card fraud detection system based on federated learning, which can balance
the positive and negative samples in credit card transaction data, protect the privacy of bank data, and effectively improve the accuracy and
efficiency of fraud detection.

Keywords


Federated learning; Privacy protection; Fraud detection

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References


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