High-precision anomaly detection method based on Internet of Things

Abstract

The invention belongs to the technical field of Internet of Things anomaly detection, and particularly relates to an Internet of Things-based high-precision anomaly detection method based on a convolutional neural network. The method comprises the steps of inputting to-be-detected Internet of Things data, and dividing the data into a test data set and a training data set; processing features in the Internet of Things to be detected digitally through one-hot coding; standardizing the Internet of Things data to be detected; establishing a convolutional neural network model; compressing the sparse vector subjected to one-hot coding digital processing into a dense vector through an embedded layer; inputting the training data set into a convolutional neural network model for training; and inputting the test data set into the convolutional neural network model which is judged to be qualified to obtain a detection data result. The invention is higher in anomaly detection accuracy, shorter inmodel training time and higher in prediction precision, and can be widely applied to the aspects of anomaly detection of the Internet of Things and the like.

Description

technical field [0001] The invention belongs to the technical field of anomaly detection of the Internet of Things, and in particular relates to a high-precision anomaly detection method based on the Internet of Things based on a convolutional neural network. Background technique [0002] At present, the Internet of Things is mainly used in the industrial field, and also serves as a new driving force for other industries, such as smart cities and smart homes, providing an open and shared platform for massive information resources, service resources, and application resources. Through the Internet of Things platform, all users can interact with devices within the scope of authority, and Internet of Things resources are widely used. The size of the global Internet of Things continues to expand, rising from $50 billion in 2008 to nearly $151 billion in 2018. The penetration rate of Internet of Things technology in various industries is accelerating. While generating new techno...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a high-precision anomaly detection method based on the Internet of Things that overcomes the problems of the existing system, such as the excessively long issuance processing time, the inability to effectively detect abnormalities on massive data, and the high distortion rate of analysis after data extraction.

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