DocumentCode
1999764
Title
Application of Radial Function Neural Network in Network Security
Author
Niu, Yi ; Peng, Yichun
Author_Institution
Dept. of Comput. & Inf. Sci., Dongguan Univ. of Technol., Dongguan, China
Volume
1
fYear
2008
fDate
13-17 Dec. 2008
Firstpage
458
Lastpage
463
Abstract
With the widespread application of large and complicated network, network safety has become an important issue. In this paper, a security operation center (SOC) concept based on multi-sensor data fusion technology is presented from the viewpoint of the network security. A structure of a SOC system based on radial basis function neural (RBFN) network is proposed, and the detailed method of data fusion in SOC is discussed. A prototype of SOC system is developed according to this structure of the SOC, Experimental results indicate that the SOC system based on RBFN network can increase greatly the correctness of detection intrusion and decrease the rate of false positive.
Keywords
radial basis function networks; security of data; sensor fusion; data fusion; detection intrusion; multi-sensor data fusion; network safety; network security; radial function neural network; security operation center; Application software; Computer networks; Computer security; Data security; Databases; Information science; Information security; Intelligent sensors; Neural networks; Sensor phenomena and characterization; Network Security; RBF; Security Operation Center;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Security, 2008. CIS '08. International Conference on
Conference_Location
Suzhou
Print_ISBN
978-0-7695-3508-1
Type
conf
DOI
10.1109/CIS.2008.163
Filename
4724693
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