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Intelligent service anomaly detection method based on layered graph deviation network

An intelligent service and deviation technology, applied in the detection field, can solve problems such as low accuracy, lack of consideration of device data correlation, high energy consumption of data transmission in the intelligent service system, and achieve the effect of ensuring accuracy and reducing energy consumption of data transmission

Pending Publication Date: 2022-07-01
CHINA UNIV OF GEOSCIENCES (BEIJING)
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

Although this method takes into account the differences between the data of each device, it does not consider the correlation between the data of the devices, resulting in low detection accuracy.
[0004] Moreover, when the abnormality detection device detects the abnormality of the data of the devices in the intelligent service system, in the prior art, each device in the intelligent service system needs to transmit its own data to the abnormality detection device, causing the intelligent service system to High energy consumption for data transmission

Method used

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  • Intelligent service anomaly detection method based on layered graph deviation network
  • Intelligent service anomaly detection method based on layered graph deviation network
  • Intelligent service anomaly detection method based on layered graph deviation network

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Experimental program
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Embodiment 1

[0086] In order to facilitate the understanding of this embodiment, a method for detecting an abnormality of an intelligent service based on a hierarchical graph deviation network disclosed in the embodiment of this application is first introduced in detail. figure 1 A flowchart of a method for detecting anomalies in intelligent services based on a hierarchical graph deviation network provided by an embodiment of the present application is shown, as shown in FIG. figure 1 As shown, the following steps S101-S103 are included:

[0087] S101: Receive first environment data obtained by monitoring the external environment in the first time period by the central device and the first peripheral device in the device group monitoring the target object; any difference between any different devices in the same device group The similarity of the data changes between the two devices is greater than the preset value; the reference similarity of the central device is greater than the referen...

Embodiment 2

[0184] Based on the same technical concept, the embodiments of the present application also provide an intelligent service abnormality detection device based on a hierarchical graph deviation network, Figure 4 A schematic structural diagram of an intelligent service anomaly detection device based on a hierarchical graph deviation network provided by an embodiment of the present application is shown, as shown in FIG. Figure 4 As shown, the device includes:

[0185] The first receiving unit 401 is configured to receive the first environment data obtained by the central device and the first peripheral device in the device group monitoring the target object respectively monitoring the external environment within the first time period; the same device group The similarity of the data changes between any different devices within is greater than the preset value; the reference similarity of the central device is greater than the reference similarity of other devices; the reference ...

Embodiment 3

[0218] Based on the same technical concept, the embodiments of the present application also provide an electronic device, Figure 5 A schematic structural diagram of an electronic device provided by an embodiment of the present application is shown, such as Figure 5 As shown, the electronic device 500 includes: a processor 501, a memory 502 and a bus 503, the memory stores machine-readable instructions executable by the processor, and when the electronic device is running, the processor 501 and the memory 502 communicate through the bus 503 , the processor 501 executes machine-readable instructions to perform the method steps described in the first embodiment.

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Abstract

The invention provides an intelligent service anomaly detection method based on a hierarchical graph deviation network, and the method comprises the steps: receiving first environment data obtained by monitoring an external environment through a central device and a first peripheral device in a device group for monitoring a target object in a first time period; according to the first environment data of the central equipment and the first environment data of the first peripheral equipment, predicting first predicted environment data generated by the central equipment at a first moment after the first time period; calculating a first deviation value between received first target environment data obtained by monitoring the external environment by the central equipment at the first moment and the predicted first predicted environment data; the first deviation value is used for judging whether the first target environment data monitored by the equipment in the equipment group at the first moment is abnormally changed or not. Through the method, the data transmission energy consumption can be reduced.

Description

technical field [0001] The present application relates to the field of detection technology, and in particular, to a method for detecting anomalies in intelligent services based on a hierarchical graph deviation network. Background technique [0002] When performing anomaly detection on data generated by various devices (such as sensor devices) in an intelligent service system, there are two situations in the prior art. The first situation is an anomaly detection method based on univariate time series modeling, specifically , by building a detection model, and using the detection model to detect anomalies in the data generated by each device, that is to say, the detection model needs data applicable to each device in the intelligent service system, and the detection model is used for each device in the detection model. The detection method of each device data is the same (for example, when the intelligent service system is a fire alarm detection system, the detection model n...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/213G06F18/22G06F18/2433
Inventor 周长兵郭宏泰施振生张玉清
Owner CHINA UNIV OF GEOSCIENCES (BEIJING)