Research on Intelligent Detection of Intrusion Data in Network
Autor: | Honglei Yao, Guangjie Zhu |
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Rok vydání: | 2020 |
Předmět: |
Consumption (economics)
Artificial neural network business.industry Computer science Network security 010401 analytical chemistry 02 engineering and technology 021001 nanoscience & nanotechnology Machine learning computer.software_genre 01 natural sciences Telecommunications network 0104 chemical sciences Data modeling Intrusion Artificial intelligence 0210 nano-technology business computer |
Zdroj: | 2020 Chinese Automation Congress (CAC). |
DOI: | 10.1109/cac51589.2020.9326803 |
Popis: | The typical algorithms in machine learning and data mining are described and compared based on the advantages from individual algorithm including computation consumption and computation capacities. Based on the research on the novel academic paper, the problems to be solved are analyzed in network security. Besides, some suggestions are provided to adapt to specific scenarios. |
Databáze: | OpenAIRE |
Externí odkaz: |
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