Research on Network Abnormal Behavior Recognition Model Based on Parallel Decision Tree Algorithm
Pages 69 - 74
Abstract
As the network is more and more inseparable from people's life, network security has become very important. Nowadays, in the face of a large number of network attacks, effective network attack identification means is particularly important. Therefore, this paper proposes a new parallel structure model based on decision tree, which improves the traditional binary decision tree network. At the same time, it combines the ensemble learning model to avoid the local optimal solution problem and improve the accuracy of network attack recognition. When encountering a large amount of network traffic data, the identification time of network traffic monitoring is greatly shortened. Combined with the simulation experiment to complete the relevant verification, the simulation results show that the model proposed in this paper can greatly shorten the attack recognition time on the basis of ensuring the accuracy of network attack recognition, which provides an important guarantee for network attack and defense.
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Published In
September 2023
137 pages
ISBN:9798400700576
DOI:10.1145/3629264
Copyright © 2023 ACM.
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Association for Computing Machinery
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Published: 19 December 2023
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ICCDA 2023
ICCDA 2023: 2023 The 7th International Conference on Computing and Data Analysis
September 15 - 17, 2023
Guiyang, China
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