期刊
SCIENTIFIC PROGRAMMING
卷 2022, 期 -, 页码 -出版社
HINDAWI LTD
DOI: 10.1155/2022/1687400
关键词
-
资金
- Ministry of Education of Science and Technology Development Center of Production Innovation Fund China's Colleges and Universities
- [2020 IT A07027]
With the rapid development of Internet technology in recent years, network security has become an increasingly important issue. Data mining technology has been widely used in processing network information. Rough set data mining, as a method to directly analyze and reason data, has unique advantages in information processing by discovering implicit knowledge and revealing potential laws. Therefore, it is of great significance to conduct research on monitoring network security information system based on rough set data mining.
In recent years, with the explosive development of Internet technology, network security has gradually become a hot issue. At present, data mining technology has been widely used in processing network information. Rough set theory is a natural data mining or knowledge discovery method because the purpose and starting point of the research is to directly analyze and reason the data, discover the implicit knowledge and reveal the potential laws. Rough set data mining has unique advantages in processing information, so it is necessary to carry out research on monitoring network security information system based on rough set data mining. The purpose of this article is to solve how to implement network security problems of information system of monitoring, through research the related contents of rough set data mining technology, based on the two kinds of data pre-processing algorithm, data mining based on rough sets is discussed in detail the two kinds of data pre-processing algorithm in network security information system monitoring, especially the feasibility of the invasive monitoring. The results show that the two data pre-processing algorithms based on rough set data mining can effectively realize the monitoring function of common network security information system and improve the security of network security information system to some extent. The simulation results show that the monitoring accuracy of these two data pre-processing algorithms in the common network security information system is as high as 98.5%, which is about 12% higher than the accuracy of the general system.
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