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Prediction and Analysis of Network Information Security Risk Based on Convolutional Neural Network

Published: 22 November 2021 Publication History

Abstract

As an important part of computer network security system, network information security is not only related to the security of computer stored information, but also affects the construction of computer network environment. Aiming at the problem of network information security risk prediction, this paper proposes a network information security risk prediction method based on Convolutional Neural Network (CNN). In this model, batch normalization of data is added to CNN at each layer, and then the final classification results are obtained through the full connection layer of the network. Based on the established risk prediction index system for network information security system, combined with the CNN prediction model, a network information security system is simulated, and the effectiveness of the proposed model is verified by experiments.

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  1. Prediction and Analysis of Network Information Security Risk Based on Convolutional Neural Network

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    ICISCAE 2021: 2021 4th International Conference on Information Systems and Computer Aided Education
    September 2021
    2972 pages
    ISBN:9781450390255
    DOI:10.1145/3482632
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Published: 22 November 2021

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