Computer network security evaluation model based on neural network

2019 ◽  
Vol 37 (1) ◽  
pp. 71-78 ◽  
Author(s):  
Xinwei Li ◽  
Hui Chen ◽  
Bryan Ariann
Keyword(s):  
Neural Network ◽  
Network Security ◽  
Computer Network ◽  
Evaluation Model ◽  
Security Evaluation ◽  
Model Based ◽  
Computer Network Security

Research on Application of Neural Network in Computer Network Security Evaluation

2014 ◽  
Vol 8 (1) ◽  
pp. 766-771
Author(s):  
Shujuan Jin
Keyword(s):  
Neural Network ◽  
Network Security ◽  
Evaluation System ◽  
Evaluation Method ◽  
Computer Network ◽  
Evaluation Model ◽  
Indicator System ◽  
Security Evaluation ◽  
Model Based ◽  
Computer Network Security

Purpose: discuss the role of the neural network (NN) theory in the computer network security evaluation. Method: propose three-level and four-class indicator system suitable for network security evaluation, establish the network security evaluation system model based on NN, optimize the NN model by using the particle swarm, collect 100- group data on the computer network security evaluation of different scales via expert scoring, and normalize them; Result: the evaluation model based on NN is simple and practicable to network security evaluation and can eliminate disturbance of the subjective factors of the human being. The simulation results indicate that the system can reduce relative output error and improve correctness rate of evaluation. Conclusion: The NN model is very valuable in research on the computer network security evaluation system, which can offset weaknesses of the past evaluation methods to some extent, improve precision of the evaluation results, and provide reference to prediction and control of the network security problems in future.

Researches on the Network Security Evaluation Method Based on BP Neural Network

2014 ◽  
Vol 686 ◽  
pp. 470-473 ◽  
Author(s):  
Yi Bin Zhang ◽  
Ze Quan Yan
Keyword(s):  
Neural Network ◽  
Network Security ◽  
Bp Neural Network ◽  
Evaluation Method ◽  
Computer Network ◽  
Evaluation Model ◽  
Evaluation Index System ◽  
Security Evaluation ◽  
Computer Network Security ◽  
Neural Network Algorithm

This paper first describes the basic theory of BP neural network algorithm, defects and improved methods, establishes a computer network security evaluation index system, explores the computer network security evaluation method based on BP neural network, and has designed to build the evaluation model, and shows that the method is feasible through the MATLAB simulation experiments.

Fuzzy Comprehensive Evaluation Model of Computer Network Security and its Application

2014 ◽  
Vol 711 ◽  
pp. 286-292 ◽  
Author(s):  
Yan Huang ◽  
Jia Qiang E ◽  
Chen Tao ◽  
Zhi Qiang Wang
Keyword(s):  
Network Security ◽  
Computer Network ◽  
Fuzzy Theory ◽  
Fuzzy Ahp ◽  
Evaluation Model ◽  
Fuzzy Comprehensive Evaluation ◽  
Security Evaluation ◽  
Security Assessment ◽  
Fuzzy Evaluation ◽  
Computer Network Security

Network security assessment is a complex multi-criteria problem including both quantitative and qualitative factors. In this paper, taken the computer network security evaluation index for a research object, the judgment matrix of index weight was improved based on the fuzzy theory, and a new weight determination approach was proposed to make up the shortcomings of traditional weight determination method and highlight the fuzziness of expert judgment. Meanwhile using fuzzy theory to establish fuzzy evaluation matrix, then combine analytic hierarchy process to set up a fuzzy AHP evaluation model of the computer network security. At the final stage, a security assessment of the system of an institution’s network was to implement to demonstrate the feasibility of the evaluation model.

Methods for evaluating the computer network security with fuzzy number intuitionistic fuzzy dual Hamy mean operators

2020 ◽  
Vol 39 (3) ◽  
pp. 4427-4441
Author(s):  
Bin Xu
Keyword(s):  
Network Security ◽  
Membership Function ◽  
Fuzzy Number ◽  
Fuzzy Numbers ◽  
Computer Network ◽  
Information Aggregation ◽  
Security Evaluation ◽  
Uncertain Information ◽  
Intuitionistic Fuzzy ◽  
Computer Network Security

The concept of fuzzy number intuitionistic fuzzy sets (FNIFSs) is designed to effectively depict uncertain information in decision making problems which fundamental characteristic of the FNIFS is that the values of its membership function and non-membership function are depicted with triangular fuzzy numbers (TFNs). The dual Hamy mean (DHM) operator gets good performance in the process of information aggregation due to its ability to capturing the interrelationships among aggregated values. In this paper, we used the dual Hamy mean (DHM) operator and dual weighted Hamy mean (WDHM) operator with fuzzy number intuitionistic fuzzy numbers (FNIFNs) to propose the fuzzy number intuitionistic fuzzy dual Hamy mean (FNIFDHM) operator and fuzzy number intuitionistic fuzzy weighted dual Hamy mean (FNIFWDHM) operator. Then the MADM methods are proposed along with these operators. In the end, we utilize an applicable example for computer network security evaluation to prove the proposed methods.

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