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Internet Banking Fraud Detection Using Deep Learning Based on Decision Tree and Multilayer Perceptron

机译:基于决策树的深度学习和多层情人的互联网银行欺诈检测

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Fraud transactions have become a growing problem in the online banking sphere. As technology progresses, fraudsters also change their methods of committing fraud. There are also emerging technologies that allow fraudsters to mimic the transaction behavior of genuine customers and they also keep changing their methods so that it is difficult to detect fraud. This paper discusses the importance of fraud detection methods and compares Hidden Markov Model, Deep Learning, and Neural Network that are used to detect fraud in online banking transactions.
机译:欺诈事务已成为网上银行领域的不断增长的问题。随着技术的进步,欺诈者还改变了他们的欺诈方法。还有新兴的技术可以让欺诈者模仿真正客户的交易行为,他们也在继续改变他们的方法,以便难以检测欺诈。本文讨论了欺诈检测方法的重要性,并比较了用于检测在线银行交易中欺诈的隐性马尔可夫模型,深度学习和神经网络。

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