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

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...

AI Technical Summary

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. Obviously, the traditional method does not have a self-renewal mechanism that adapts to the environment, and there is a certain lag. Manually adjusting the model requires a lot of operations and Maintenance costs, so there is an urgent need for a network payment fraud detection method that can automatically learn and adapt to environmental changes to solve these problems

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