Application of Artificial Intelligence Technology in Computer Network Security Communication

In order to cope with the frequent challenges of network security issues, a method of applying artificial intelligence technology to computer network security communication is proposed. First, within the framework of computer network communication, an intelligent protocol reverse analysis method is...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Journal of control science and engineering Ročník 2022; s. 1 - 6
Hlavní autor: Li, Fulin
Médium: Journal Article
Jazyk:angličtina
Vydáno: New York Hindawi 21.07.2022
John Wiley & Sons, Inc
Wiley
Témata:
Algorithms
Artificial intelligence
Artificial neural networks
Automation
Communication
Computer networks
Grammar
Medical diagnosis
Model testing
Neural networks
Reverse engineering
Semantics
Syntax
ISSN:1687-5249, 1687-5257
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:In order to cope with the frequent challenges of network security issues, a method of applying artificial intelligence technology to computer network security communication is proposed. First, within the framework of computer network communication, an intelligent protocol reverse analysis method is proposed. By converting the protocol into an image and establishing a convolutional neural network model, artificial intelligence technology is used to map the data to the protocol result. Finally, use the model to test the test data to adjust the model parameters and optimize the model as much as possible. The experimental results show that compared with the test model, the results obtained after training with the deep convolutional neural network model in this paper have increased the accuracy by 2.4%, reduced the loss by 38.2%, and reduced the running time by 42 times. The correctness and superiority of the algorithm and model are verified.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:1687-5249
1687-5257
DOI:10.1155/2022/9785880