A New Network Security Evaluation Model Based on Multi-Data and Layer

2011 ◽  
Vol 474-476 ◽  
pp. 1440-1446
Author(s):  
Xiao Hu Ma
Keyword(s):  
Network Security ◽  
Risk Evaluation ◽  
Evaluation System ◽  
Evaluation Model ◽  
Security Evaluation ◽  
Model Based ◽  
Valuation Model ◽  
Network Safety ◽  
Network Risk ◽  
Risk Evaluation System

The last few years, research on network risk evaluation technique[1], and establishment of risk evaluation system facing integrity grade protection is the hot problem. There is great significance. The existing network safety valuation system exists many blemishes in science, and nationality, etc. Such as pole light, Nessus, Anluo network risk valuation system etc, they evaluate only from loophole scan or permeating test etc. There Lack important contents, for example, the safe grade and safety of target management strategy of the evaluation network. The standards, such as CC and OB 17859, OBIT 18336, OBIT 20984[2] etc ,are the outline requests , don't have easy operability. The existing network safety valuation methods and models, for example, network safety valuation model based on the discharge attack judges[3] , visit control model[4], network safety valuation model based on the diagram talks[5], all have blemish, there have a few evaluate objects, it's strong to limit, the function is bad. To resolve the above problem, this paper provides a model named NSEMML (Network Security Evaluation Model based on Multi-data and Layer), And a new risk evaluation system based on FNSEM is developed.

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.

A Design of the Network Security Evaluation System

2014 ◽  
Vol 686 ◽  
pp. 458-462
Author(s):  
Zi Yan Shi ◽  
Guo Lin Zhao ◽  
Qiao Lin Hu
Keyword(s):  
Network Security ◽  
Evaluation System ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Normal Operation ◽  
Management Tool ◽  
Security Evaluation ◽  
Security Risk ◽  
Security Threat ◽  
Management Tools

The security evaluation for an information network system is an important management tool to insure its normal operation. We must realize the significance of the comprehensive network security risks. A network evaluation model and the algorithm are presented and adapt the hierarchical method to characterize the security risk situation. The evaluation method is used to evaluate the key nodes and the mathematics is used to analyze the whole network security situation. Compared with others, the method can automatically create a rule-based security evaluation model to evaluate the security threat from the individual security elements and the combination of security elements, and then evaluation the network situation. It is shown that this system provides a valuable model and algorithms to help to find the security rules, adjust the security measure, improve the security performance and design the appropriate security risk evaluation and management tools.

scholarly journals A Quantitative Risk Evaluation Model for Network Security Based on Body Temperature

2016 ◽  
Vol 2016 ◽  
pp. 1-10
Author(s):  
Y. P. Jiang ◽  
C. C. Cao ◽  
X. Mei ◽  
H. Guo
Keyword(s):  
Immune System ◽  
Body Temperature ◽  
Network Security ◽  
Real Time ◽  
Risk Evaluation ◽  
Evaluation Model ◽  
Antibody Concentration ◽  
Security Risk ◽  
Network Risk ◽  
Risk Evaluation Model

These days, in allusion to the traditional network security risk evaluation model, which have certain limitations for real-time, accuracy, characterization. This paper proposed a quantitative risk evaluation model for network security based on body temperature (QREM-BT), which refers to the mechanism of biological immune system and the imbalance of immune system which can result in body temperature changes, firstly, through ther-contiguous bits nonconstant matching rate algorithm to improve the detection quality of detector and reduce missing rate or false detection rate. Then the dynamic evolution process of the detector was described in detail. And the mechanism of increased antibody concentration, which is made up of activating mature detector and cloning memory detector, is mainly used to assess network risk caused by various species of attacks. Based on these reasons, this paper not only established the equation of antibody concentration increase factor but also put forward the antibody concentration quantitative calculation model. Finally, because the mechanism of antibody concentration change is reasonable and effective, which can effectively reflect the network risk, thus body temperature evaluation model was established in this paper. The simulation results showed that, according to body temperature value, the proposed model has more effective, real time to assess network security risk.

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