Anomaly detection method and device, electronic equipment and storage medium
An anomaly detection and anomaly technology, applied in the Internet field, can solve the problems of poor accuracy of abnormal reconstruction error threshold and affect the accuracy of anomaly detection, so as to achieve the effect of improving accuracy and eliminating deviation
Active Publication Date: 2020-12-29
NEW H3C BIG DATA TECH CO LTD
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[0004] However, because the above-mentioned abnormal reconstruction error threshold is determined according to the preset quantile set artificially, and the preset quantile corresponding to different data cannot be accurately determined artificially, resulting in the The accuracy of the determined anomaly reconstruction error threshold is poor, thus affecting the accuracy of anomaly detection
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[0067]The technical solutions in the embodiments of the present application will be described clearly and completely in conjunction with the accompanying drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in this application, all other embodiments obtained by those of ordinary skill in the art without creative work fall within the protection scope of this application.
[0068]In the related art, when using the VAE anomaly detection method to perform anomaly detection, there is a problem that the accuracy of the abnormal reconstruction error threshold is poor, which affects the accuracy of anomaly detection. For ease of understanding, the following combinationFigure 1-a ,Figure 1-b withFigure 1-c The VAE anomaly detection process in related technologies is explained. among them,Figure 1-a Is the first structural diagram of the...
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The embodiment of the invention provides an anomaly detection method and device, electronic equipment and a storage medium. According to the scheme, the method comprises the following steps: traininga VAE model by utilizing multiple sample data included in a preset training set; respectively inputting the plurality of sample data into a trained VAE model to obtain first output data correspondingto each sample data; determining a reconstruction error probability density distribution curve according to a first reconstruction error between each piece of sample data and the first output data corresponding to each piece of sample data; determining a first reconstruction error corresponding to a target inflection point in the reconstruction error probability density distribution curve as an abnormal reconstruction error threshold; and performing anomaly detection on the to-be-detected data according to the anomaly reconstruction error threshold and the trained VAE model. Through the technical scheme provided by the embodiment of the invention, the accuracy of the determined abnormal reconstruction error threshold value is improved, so that the accuracy of anomaly detection is improved.
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Technical field[0001]This application relates to the field of Internet technology, and in particular to an abnormality detection method, device, electronic equipment, and storage medium.Background technique[0002]In the process of anomaly detection, due to the lack of abnormal sample data, the use of supervised anomaly detection methods is restricted. Therefore, unsupervised anomaly detection methods are often used for anomaly detection in related technologies. For example, in the field of intelligent operation and maintenance, various operation and maintenance indicators are detected through unsupervised anomaly detection methods to determine abnormal data.[0003]At present, the Variational Auto-Encoder (VAE) anomaly detection method is one of the most promising unsupervised anomaly detection methods. Specifically, the data to be detected is input into the trained VAE model, and the encoder in the VAE model extracts the distribution characteristics of the input data to be detected to...
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IPC IPC(8): G06K9/62G06N20/20
CPCG06N20/20G06F18/2321G06F18/214
Inventor 史艳华
Owner NEW H3C BIG DATA TECH CO LTD