期刊
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS
卷 39, 期 6, 页码 8633-8642出版社
IOS PRESS
DOI: 10.3233/JIFS-189259
关键词
SVM; Balanced binary decision; internet of things security; intrusion detection; COVID-19
资金
- Jilin Science and technology development plan project
- natural science foundation project titled research on monitoring technology of ginseng growth environment parameters by wireless sensor network [20150101099jc]
- Jilin province newinterdisciplinary digital agriculture cultivation project titled recognition algorithm research based on NSST deep learning
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.
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