Network security threat assessment model based on fuzzy algorithm

2011 ◽  
Author(s):  
Fakariah Hani Mohd Ali ◽  
Wan Mohd Nadzir Hadzril Wan Ismail
Keyword(s):  
Network Security ◽  
Threat Assessment ◽  
Assessment Model ◽  
Security Threat ◽  
Fuzzy Algorithm ◽  
Model Based

scholarly journals Research on the Key Technologies of Network Security-Oriented Situation Prediction

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yikun Zhu ◽  
Zhiling Du
Keyword(s):  
Network Security ◽  
Situational Awareness ◽  
Algorithm Design ◽  
Evidence Theory ◽  
Assessment Model ◽  
Time Varying ◽  
Security Threat ◽  
Model Based ◽  
Posture Assessment ◽  
Threat Posture

In today’s increasingly severe network security situation, network security situational awareness provides a more comprehensive and feasible new idea for the inadequacy of various single solutions and is currently a research hotspot in the field of network security. At present, there are still gaps or room for improvement in network security situational awareness in terms of model scheme improvement, comprehensive and integrated consideration, algorithm design optimization, etc. A lot of scientific research investments and results are still needed to improve the form of network security in a long and solid way. In this paper, we propose a network security posture assessment model based on time-varying evidence theory for the existing multisource information fusion technology that lacks consideration of the problem of threat occurrence support rate over time and make the threat information reflect the law of time change by introducing a time parameter in the basic probability assignment value. Thus, the existing hierarchical threat posture quantitative assessment technique is improved and a hierarchical multisource network security threat posture assessment model based on time-varying evidence theory is proposed. Finally, the superiority of the proposed model is verified through experiments.

Research on Intrusion Detection Method Based on Neural Network

2011 ◽  
Vol 403-408 ◽  
pp. 1483-1486
Author(s):  
Chi Xu ◽  
Wen Fang Zhang
Keyword(s):  
Risk Assessment ◽  
Network Security ◽  
Security Analysis ◽  
Assessment Model ◽  
Security Assessment ◽  
Security Risk ◽  
Analysis Model ◽  
Model Based ◽  
Security Risk Assessment ◽  
Meaningful Definition

The research of this dissertation focuses on the quantitative methodologies of the network security assessment. So the dissertation gives the term “Model-based network security risk assessment” a more meaningful definition. The methodology called a model-based will use one network security analysis model to design the scenarios of threatens according to the Patterns behaviors of vulnerabilities and threatens in the network. And then the risk assessment will be done under those scenarios. Following this new definition. The dissertation Proposes a Component-centric Access Graph Based Network Security Risk Assessment Model (Oc-AGNSRAM).

An Evaluation Method for Information Security Level Based on OWA Operator and Bayesian Network

2013 ◽  
Vol 411-414 ◽  
pp. 72-75
Author(s):  
Ke He Wu ◽  
Shi Chao Ye ◽  
Yu Guang Niu
Keyword(s):  
Information System ◽  
Information Security ◽  
Bayesian Network ◽  
Threat Assessment ◽  
Objective Evaluation ◽  
Assessment Model ◽  
Owa Operator ◽  
Security Threat ◽  
Threat Level ◽  
System Threat

Analysis of information security threats in the system elements and assessment process, the decision-maker's subjective judgment threat level information and to obtain an objective evaluation by testing different forms of information and data, it is difficult for a direct threat assessment, proposed based on Bayesian network and OWA operator information security threat assessment model. First, combined with expert knowledge Bayesian network inference rules introduced conditional probability matrix, in order to build an information security threat assessment model. Secondly, based on OWA operator build the expert group decision making information system threat level of the target's subjective judgment information, and as a Bayesian network model of the target information system threat level of a priori information, and objective evaluation of information as a shell Julius observation node network model, which integrates the subjective and objective information security threat level. Finally, a simulation example shows that the model is reasonable and effective.

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