Anomaly detection method of industrial control network signal based on deep learning structure

An industrial control network and deep learning technology, applied in the field of outlier detection in industrial control network data, can solve problems such as difficult detection of a small number of outliers, and achieve the effect of improved ability
CN109034140BActive Publication Date: 2021-05-04HARBIN INST OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
HARBIN INST OF TECH
Publication Date
2021-05-04

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Abstract

The invention provides an abnormal detection method for industrial control network signals based on a deep learning structure, and relates to the technical field of abnormal value detection in industrial control network data. The present invention aims to solve the problem that it is difficult to detect a small amount of abnormal values ​​because it needs to be artificially defined for distinguishing normal data and abnormal values ​​in the existing methods. Select part of the data from the industrial control network data as a training sample, perform data normalization and standardization operations on the training sample, obtain the normalized calibrated data, and use the data enhancement algorithm to add some false positives to the normalized calibrated data The sample values ​​form the detected data; the normal data and the detected data are input into an autoencoder compression network for training, and the trained data are obtained respectively; the data are input into the comparison network and calculated by the deep neural network to obtain The distance between the normal data and the detected data, using a classifier to determine the abnormal value in the detected data according to the distance. It is used for signal anomaly detection.
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Description

technical field

[0001] The invention relates to an industrial control network signal abnormality detection method based on a deep learning structure, and belongs to the technical field of abnormal value detection in industrial control network data. Background technique

[0002] Industrial Control System (Industrial Control System, ICS) refers to an automatic control system composed of computers and industrial process control components, which consists of controllers, sensors, transmitters, actuators, and input / output interfaces. These components are connected through industrial communication lines according to a certain communication protocol to form an industrial manufacturing or processing system with automatic control capabilities.

[0003] The current industrial control system usually involves the following types of networks during specific deployment: enterprise office network (enterprise network or office network), process control and monitoring network (monitoring net...

Claims

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