Research on prediction technique of network situation awareness

Author

Wang, Juan ; Qin, Zhi-guang ; Ye, Li

Author_Institution

Sch. of Comput. Sci. & Eng., Univ. of Electron. Sci. & Technol., Chengdu

fYear

2008

fDate

21-24 Sept. 2008

Firstpage

570

Lastpage

574

Abstract

In this paper we study on the prediction technique of network situation awareness. It has two levels: the high-level situation and the low-level next attack step. The first one includes the indexes and the evaluation results of the network security situation, they are figure form, we use the RBF network to predict them for RBFpsilas self-learning character. Then we use the weighted attack graph to predict the next attack step. The weights represent the probability; the biggest weights indicate the most possible next attack step. The simulations show these prediction methods can offer different prediction capability to satisfy the prediction need of the network situation awareness.

Keywords

directed graphs; learning (artificial intelligence); probability; radial basis function networks; security of data; RBF network; RBF self-learning character; low-level next attack step; network situation awareness prediction technique; probability; radial basis function network; weighted attack graph; Computer science; Data security; Decision making; Information security; Intrusion detection; Monitoring; Neural networks; Prediction methods; Predictive models; Radial basis function networks; RBF neural network; alert analysis; network situation awareness;

fLanguage

English

Publisher

ieee

Conference_Titel

Cybernetics and Intelligent Systems, 2008 IEEE Conference on

Conference_Location

Chengdu

Print_ISBN

978-1-4244-1673-8

Electronic_ISBN

978-1-4244-1674-5

Type

conf

DOI

10.1109/ICCIS.2008.4670783

Filename

4670783