Secret information security system in computer network based on Bayesian classification and nonlinear algorithm
Abstract: To solve the problem that most computer network security assessment systems cannot comprehensively analyze data, this article proposes a research method for computer network confidentiality information security system based on the Bayesian classification algorithm. This research takes the computer network security secret-related information security as the core, cleverly uses the EBCA back-propagation model, and comprehensively uses nonlinear functions to propose a computer network secret-related information security application system considering EBCA, which effectively solves the complex cross-linking relationship. The effectiveness of the method is verified by simulation experiments. Simulation experiments show that when the network performance is in the optimal state, the slope is 1, the intercept is 0, and the fitting degree is 1. The method proposed in this article is especially suitable for the nonlinear characteristics of computer network security and can accurately, comprehensively, and systematically reflect the security operation status of network security and confidential information. Then, through the simulation test, it is found that the method in this study can effectively meet the error requirements of equipment integrity and equipment normal rate.
- Location
-
Deutsche Nationalbibliothek Frankfurt am Main
- Extent
-
Online-Ressource
- Language
-
Englisch
- Bibliographic citation
-
Secret information security system in computer network based on Bayesian classification and nonlinear algorithm ; volume:11 ; number:1 ; year:2022 ; pages:620-628 ; extent:9
Nonlinear engineering ; 11, Heft 1 (2022), 620-628 (gesamt 9)
- Creator
-
Wu, Hao
- DOI
-
10.1515/nleng-2022-0237
- URN
-
urn:nbn:de:101:1-2022112213021671567431
- Rights
-
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
-
15.08.2025, 7:36 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Wu, Hao
Other Objects (12)
TNF Receptor Associated Factors
Gevrey smooth topology is proper to detect normalization under Siegel type small divisor conditions
Extraction of knowledge on spatial distribution and spatial relationship from scanned topographic map using Convolutional Neural Networks
Analysis and simulation for an isotropic phase-field model describing grain growth
The term structure of inflation expectations
Application of mechanochemical synthesis of advanced materials
TOAST: improving reference-free cell composition estimation by cross-cell type differential analysis
Accounting for cell type hierarchy in evaluating single cell RNA-seq clustering
Intersections of SLE Paths: the double and cut point dimension of SLE
Topographic analysis supported by a knowledge graph: A case of ridge landscape recognition
On Invariant Tori with Prescribed Frequency in Hamiltonian Systems
Uniqueness of global weak solutions for the general Ericksen–Leslie system with Ginzburg–Landau penalization in $$\mathbb T}}^2$$ T 2
TNF Receptor Associated Factors
Gevrey smooth topology is proper to detect normalization under Siegel type small divisor conditions
Extraction of knowledge on spatial distribution and spatial relationship from scanned topographic map using Convolutional Neural Networks
Analysis and simulation for an isotropic phase-field model describing grain growth
The term structure of inflation expectations
Application of mechanochemical synthesis of advanced materials
TOAST: improving reference-free cell composition estimation by cross-cell type differential analysis
Accounting for cell type hierarchy in evaluating single cell RNA-seq clustering
Intersections of SLE Paths: the double and cut point dimension of SLE
Topographic analysis supported by a knowledge graph: A case of ridge landscape recognition
On Invariant Tori with Prescribed Frequency in Hamiltonian Systems
Uniqueness of global weak solutions for the general Ericksen–Leslie system with Ginzburg–Landau penalization in $$\mathbb T}}^2$$ T 2
TNF Receptor Associated Factors
Gevrey smooth topology is proper to detect normalization under Siegel type small divisor conditions
Extraction of knowledge on spatial distribution and spatial relationship from scanned topographic map using Convolutional Neural Networks
Analysis and simulation for an isotropic phase-field model describing grain growth
The term structure of inflation expectations
Application of mechanochemical synthesis of advanced materials
TOAST: improving reference-free cell composition estimation by cross-cell type differential analysis
Accounting for cell type hierarchy in evaluating single cell RNA-seq clustering
Intersections of SLE Paths: the double and cut point dimension of SLE
Topographic analysis supported by a knowledge graph: A case of ridge landscape recognition
On Invariant Tori with Prescribed Frequency in Hamiltonian Systems