Industrial Internet of Things data space access risk assessment method based on deep learning

Abstract

The invention discloses an industrial Internet of Things data space access risk assessment method based on deep learning, and relates to the technical field of Internet of Things access risk assessment. The method comprises the following steps: recording access behavior data of a data space, constructing a single terminal data access behavior vector, and further constructing an association topology matrix based on correlation among a plurality of terminal access vectors; and then based on a deep learning mechanism, respectively training a single-terminal access risk assessment deep learning model and a data space access risk assessment deep learning model, thereby realizing risk rating of a single-terminal access behavior and risk rating of data space data security of the Internet of Things. According to the invention, for data access of the industrial Internet of Things data space, joint assessment of terminal access and data space risks is realized, the comprehensiveness of assessment is expanded, and a deep learning mechanism is utilized, so that the accuracy of risk assessment is improved, and the operation risk of the industrial Internet of Things is reduced.

Description

Technical field [0001] The present invention relates to the field of Internet risk assessment technology, in particular, based on deep learning industrial network data space access risk assessment methods. Background technique [0002] Data information is a long-term, important business asset that has an important role in the survival of enterprises in a increasingly competitive market, which requires protection like any other form of valuable assets. The data space of manufacturing enterprises in industrial Internet of Things has the characteristics of dynamic evolution, data sharing, and there is a contradiction between enterprise data sharing and privacy. Therefore, risk assessment is an important way to address the security issues of enterprise data space, and its goal is to verify and evaluate the risk of data assets to prevent and resolve security risks, and control the risk in an acceptable level, thus maximizing Guarantee data security. [0003] Currently, how to achieve ...

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Problems solved by technology

[0006] The purpose of the present invention is to provide a risk assessment method for industrial Internet of Things data space access based on deep learning, so as to solve the problem of low accuracy and low adaptability of the risk assessment method for industrial Internet of Things data space access in the prior art. It is difficult to effectively reflect and analyze the complex relationship between

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