A hierarchical P2P model and a data fusion method for network security situation awareness system

2016 ◽  
Vol 21 (2) ◽  
pp. 126-132
Author(s):  
Fangfang Guo ◽  
Yibing Hu ◽  
Longting Xiu ◽  
Guangsheng Feng ◽  
Shuaishuai Wang
Keyword(s):  
Network Security ◽  
Data Fusion ◽  
Situation Awareness ◽  
Fusion Method ◽  
Awareness System

scholarly journals System Architecture and Key Technologies of Network Security Situation Awareness System YHSAS

2019 ◽  
Vol 59 (1) ◽  
pp. 167-180 ◽  
Author(s):  
Weihong Han ◽  
Zhihong Tian ◽  
Zizhong Huang ◽  
Lin Zhong ◽  
Yan Jia
Keyword(s):  
Network Security ◽  
Situation Awareness ◽  
System Architecture ◽  
Key Technologies ◽  
Awareness System

scholarly journals A Prediction Method of Network Security Situation based on QPSO-SVM

2020 ◽  
Vol 14 ◽  
Keyword(s):  
Network Security ◽  
Situation Awareness ◽  
Prediction Accuracy ◽  
Simulation Experiment ◽  
Prediction Method ◽  
Support Vector ◽  
Original Sequence ◽  
Vector Machines ◽  
The Face ◽  
Awareness System

In network security situation awareness system, situation prediction is the key point. The traditional intrusion detection method lacks scalability in the face of the changing network structure and lacks adaptability in the face of unknown attack types. In order to ensure and improve the accuracy of situation prediction, a QPSO-SVM prediction model is proposed by combining the optimization performance of quantum particle swarm optimization and the prediction accuracy of support vector machines. By adding the original sequence to the original sequence, this model weakens the irregular disturbance in the original sequence and enhances the regularity of the sequence. Compared with the traditional SVM and PSOSVM, the superiority of the prediction precision is better, the prediction accuracy can be ensured, and the validity of the model is tested by the simulation experiment.

scholarly journals An Alert Fusion Method Based on Grey Relation and Attribute Similarity Correlation

2016 ◽  
Vol 12 (08) ◽  
pp. 25 ◽  
Author(s):  
Wei Liang ◽  
Zuo Chen ◽  
Ya Wen ◽  
Weidong Xiao
Keyword(s):  
Network Security ◽  
Data Fusion ◽  
Large Volume ◽  
Mathematical Theory ◽  
Fusion Method ◽  
Aggregation Method ◽  
Grey Correlation ◽  
Feature Similarity ◽  
Grey Relation ◽  
Similarity Method

Various security devices which produce a large volume of logs and alerts have been used widely. It is such a troublesome and time-consuming task for network managers to analyze and deal with the information. This paper presented an improved alerts aggregation method based on grey correlation and attribute similarity method. We used grey correlation to ascertain the importance of alert attributes in network security, and considered it as the weight of attributes. Then we combined with the attribute similarity method and calculated the overall feature similarity in order to complete alert aggregation. Experiments results showed that this method had a strict mathematical theory basis and a higher practical value, which can effectively reduce raw alerts and reduce redundancy for alert data fusion.

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