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- W1978223003 abstract "In this paper, we provide some insights into analysis of fraud transaction recognition on Alipay's Money Flow Network. We first show that the Money Flow Network follows a power-law distribution on daily, monthly or yearly basis, based on which we propose a new approach of fraud transaction recognition on the Money Flow Network from two perspectives. First, the Collapse Network is identified by the discovery that fraud transaction requires a huge amount of active controlled 'zombie' accounts, which are always intentionally manipulated by fraudulent online sellers, and the collapse of the Money Flow Network emerges due to their economic inactivity; Second, we define the Activation Forest that leads to the recognition of the controlled 'zombies' even no sooner than they enter into Alipay's ecosphere. These two networks are fully explored from the perspective of detecting 'zombies', and several key features have been adopted into anti-fraud recognition. Experimental results show that our strategy is capable of effectively identifying fraud transactions on the Money Flow Network with the accuracy as high as 99.88%." @default.
- W1978223003 created "2016-06-24" @default.
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- W1978223003 date "2015-10-17" @default.
- W1978223003 modified "2023-09-28" @default.
- W1978223003 title "Fraud Transaction Recognition" @default.
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- W1978223003 doi "https://doi.org/10.1145/2806416.2806647" @default.
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