A network payment fraud detection method based on a self-learning sliding time window

A sliding time window, network payment technology, applied in the field of Internet finance, can solve the problems of a large number of operation and maintenance costs, concept drift, and hysteresis of manual adjustment models

Active Publication Date: 2019-05-17
TONGJI UNIV
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Problems solved by technology

[0003]The current traditional online payment fraud detection systems are usually time-sensitive, and the use of these single fraud detection systems does not meet the requirements of the ever-changing Internet online payment scenarios. Internet fraud The methods are full of diversity and evolution, and the user's transaction behavior pattern also has concept drift. Ob

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  • A network payment fraud detection method based on a self-learning sliding time window
  • A network payment fraud detection method based on a self-learning sliding time window
  • A network payment fraud detection method based on a self-learning sliding time window

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[0047] Embodiments of the present invention are described in detail below, examples of which are shown in the drawings, wherein the same or similar reference numerals designate the same or similar elements or elements having the same or similar functions throughout. The embodiments described below by referring to the figures are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0048] see figure 1 , the present invention a kind of network payment fraud detection method based on self-learning sliding time window, it comprises the following steps:

[0049] Step S101: Obtain a new transaction record of a certain user detected in real time, and extract features that do not depend on the sliding time window and features that depend on the sliding time window based on the transaction record and the preset sliding time window features, among which,

[0050] The features that do not depend on the sliding time window ...

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Abstract

The invention discloses a network payment fraud detection method based on a self-learning sliding time window. In order to find a more effective implementation scheme for network payment fraud detection, the method comprises the following steps of obtaining a new transaction record detected by a certain user in real time, and extracting features independent of a sliding time window and features dependent on the sliding time window based on the transaction record and a preset sliding time window; inputting the features independent of the sliding time window and the features independent of the sliding time window into the trained random forest classifier model to obtain and return the probability of fraud possibility of the transaction record. According to the present invention, the slidingtime window size is dynamically learned and adjusted through the learning automaton in reinforcement learning, and the defect that a traditional fraud detection system has lagging is overcome.

Description

technical field [0001] The invention relates to the field of Internet finance, in particular, the invention relates to a network payment fraud detection method based on a self-learning sliding time window. Background technique [0002] With the rise of the mobile Internet, various traditional businesses are gradually transferred online. Internet finance and e-commerce are developing rapidly. The generation of online payment will bring a large amount of electronic transaction data, accompanied by a large number of online payment fraud transactions. Increase. Attackers complete fraud by stealing user accounts, stealing personal privacy information, and even maliciously attacking servers. In order to ensure the security of users and the company's business, it is necessary to establish an effective network payment fraud detection system. [0003] At present, traditional online payment fraud detection systems are usually time-sensitive. Using these single fraud detection system...

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Application Information

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IPC IPC(8): G06Q20/40G06K9/62
Inventor 王成王昌琪
Owner TONGJI UNIV
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