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Prudent Fraud Detection in Internet Banking

机译:网上银行的谨慎欺诈检测

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Most commercial Fraud Detection components of Internet banking systems use some kind of hybrid setup usually comprising a Rule-Base and an Artificial Neural Network. Such rule bases have been criticised for a lack of innovation in their approach to Knowledge Acquisition and maintenance. Furthermore, the systems are brittle; they have no way of knowing when a previously unseen set of fraud patterns is beyond their current knowledge. This limitation may have far reaching consequences In an online banking system. This paper presents a viable alternative to brittleness in Knowledge Based Systems; a potential milestone in the rapid detection of unique and novel fraud patterns in Internet banking. The experiments conducted with real online banking transaction log files suggest that Prudent based fraud detection may be a worthy alternative in online banking.
机译:网上银行系统的大多数商业欺诈检测组件使用某种混合设置通常包括规则基础和人工神经网络。这些规则基础被批评,因为他们对知识获取和维护的方法缺乏创新。此外,系统易碎;他们没有办法知道以前看不见的欺诈模式的超出目前的知识。这一限制可能在网上银行系统中具有深远的影响。本文介绍了知识系统中的脆性替代品;快速检测互联网银行中独特和新型欺诈模式的潜在里程碑。使用Real网上银行交易日志文件进行的实验表明,基于谨慎的欺诈检测可能是网上银行的一个有价值的替代品。

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