A Study on Design of Early Warning Decision Support System of Desertification

Du, Junbao; Meng, Xianyong; Sun, Chengzhi; Liu, Yongqiang

doi:10.1007/978-3-642-38466-0_77

Cited by 1 publication

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“…With the development of finance industry, criminals use several means to manipulate the stock market to get benefits, so unusual transactions detection has become more important. However, hidden risks of transactions have characteristics of diversity and co-movement [1] , a flood of data are generated by transactions, and risk detection needs respond to market changes in real time, not much of a delay [2] . Moreover, traditional databases are not adapt to the operation of a large amount of data [3] , they are not optimized for real-time analysis of continuous streams and complex events [4] , and event processing over live and archived event streams has been rarely considered [5] .…”

Section: Introductionmentioning

confidence: 99%

A Monitoring Model of Unusual Transactions Based on Complex Event Processing

Liu

Zhong

2013

AMR

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Faced with the demand for real-time "big data" processing, the existing financial risk early warning systems are generally difficult to identify hidden risks in massive data information quickly and accurately. This paper introduces a complex event processing technology (CEP), proposes a method of real-time monitoring for "big data", establishes a monitoring model of unusual transactions, designs and realizes a system based on this model. The model contains data acquisition and encapsulation module, custom rules modeling module and results display module. Using real data of a security company to test the system, the results show that, it can identify hidden risks in unusual transactions accurately, and the speed of processing is improved significantly comparing with the system which is based on traditional database analysis method.

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Section: Introductionmentioning

confidence: 99%