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2020 •
An information security analysis method of Internet of things based on balanced double SVM
Authors:
Hongwei Zhu, Xuesong Wang
Abstract:
With the continuous progress of social science and technology, the development of the Internet of things is growing With the development of Internet of things, security problems emerge in endlessly During the period of COVID-19, the Internet of Things have been widely used to fight virus outbreak However, the most serious security problem of the Internet of things is network intrusion This paper proposes a balanced quadratic support vector machine information security analysis method for Internet of things Compared with the traditional support (...)
With the continuous progress of social science and technology, the development of the Internet of things is growing With the development of Internet of things, security problems emerge in endlessly During the period of COVID-19, the Internet of Things have been widely used to fight virus outbreak However, the most serious security problem of the Internet of things is network intrusion This paper proposes a balanced quadratic support vector machine information security analysis method for Internet of things Compared with the traditional support vector machine Internet of things security analysis method, this method has a higher accuracy, and can shorten the detection time, with efficient and powerful characteristics The method proposed in this paper has certain reference value to the Internet of things network intrusion problem It provides better security for the Internet of things during the protection period of covid-19 © 2020 - IOS Press and the authors All rights reserved
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External links:
OpenAIRE
Works in BIP! associated with the specified OpenAIRE research product
An information security analysis method of Internet of things based on balanced double SVM
Zhu, Hongwei, Wang, Xuesong
Journal of Intelligent & Fuzzy Systems
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2020
Computer security
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Internet privacy
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