Traffic data anomaly detection method and device

A technology for traffic data and anomaly detection, applied in the field of neural networks, can solve problems such as affecting model identification and detection and inaccurate detection results, and achieve the effect of improving accuracy and efficiency

Pending Publication Date: 2021-01-15
GUANGDONG UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Its shortcomings are: before the original data is brought into the algorithm training, there will be artificial data cleaning, data feature selection or data dimensionality reduction process; due to the existence of human subjecti

Method used

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  • Traffic data anomaly detection method and device
  • Traffic data anomaly detection method and device
  • Traffic data anomaly detection method and device

Examples

Experimental program
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Effect test

Embodiment 1

[0042] like figure 1 As shown, this embodiment provides a method for abnormal detection of traffic data, including the following steps:

[0043] S1: Input the preprocessed traffic data into the automatic encoding network model to automatically encode and decode the traffic data to obtain the reconstructed feature vector.

[0044] Wherein, the flow data may include but not limited to financial transaction data and code flow data.

[0045]It should be noted that, in an application scenario, that is, when the traffic data includes financial transaction data, implementing a traffic data anomaly detection method disclosed in the embodiment of the present invention, compared with the traditional credit evaluation system based on big data , under the premise of ensuring the integrity of the data, complex high-dimensional data can be mapped to low-dimensional vectors through the automatic coding network model, and the correlation between the internal characteristics of financial tran...

Embodiment 2

[0088] like image 3 As shown, this embodiment provides an abnormality detection device for traffic data, including a reconstruction unit 301, a feature acquisition unit 302, and a classification unit 303, wherein:

[0089] A reconstruction unit 301, configured to input the preprocessed traffic data into the automatic encoding network model, so as to automatically encode and decode the traffic data to obtain a reconstructed feature vector;

[0090] A feature acquisition unit 302, configured to input the reconstructed feature vector into the cyclic neural network model to obtain internal feature information; the internal feature information is used to represent the front-back correlation of the internal features of the traffic data;

[0091] The classification unit 303 is configured to classify the internal feature information through a Sigmoid function to obtain a binary classification result; the binary classification result is used to represent whether the traffic data is ab...

Embodiment 3

[0099] like Figure 4 As shown, this embodiment provides an electronic device, including:

[0100] A memory 401 storing executable program codes;

[0101] a processor 402 coupled to the memory 401;

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Abstract

The invention discloses a traffic data anomaly detection method and device, electronic equipment and a storage medium, and the method comprises the steps: inputting preprocessed traffic data into an automatic coding network model, so as to carry out the automatic coding and decoding of the traffic data, and obtaining a reconstruction feature vector; inputting the reconstructed feature vector intoa recurrent neural network model to obtain internal feature information, wherein the internal feature information is used for representing the front-back correlation of the internal features of the flow data; and finally, classifying the internal feature information through a Sigmoid function to obtain a dichotomy result used for representing whether the flow data is abnormal or not, so that the anomaly detection accuracy can be improved.

Description

technical field [0001] The present invention relates to the technical field of neural networks, and more specifically, to a flow data abnormality detection method and device, electronic equipment, and a storage medium. Background technique [0002] Nowadays, with the promotion and development of WeChat, Alipay, and various credit cards, more and more people choose the convenient and fast way of online transaction payment, so transaction fraud in the financial field is gradually becoming more and more , such as obtaining a credit card from a card issuing bank through stolen identity information or through a forged credit card, and then binding this type of credit card for shopping, further cashing out, etc., which will not only bring economic losses to major financial institutions , It will also have a significant negative impact on their reputation and image, so how to effectively detect these highly likely transaction frauds has become the focus of major banking and financi...

Claims

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Application Information

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IPC IPC(8): G06Q40/02G06N3/04
CPCG06N3/049G06N3/04G06N3/048G06Q40/03
Inventor 柳毅郭三田凌捷罗玉陈家辉
Owner GUANGDONG UNIV OF TECH
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