DocumentCode :
3501956
Title :
A quantitative model for network security situation awareness based on immunity and grey theory
Author :
Shi, Yuanquan ; Li, Tao ; Chen, Wen ; Zhang, Ruirui
Author_Institution :
Sch. of Comput. Sci., Sichuan Univ., Chengdu, China
Volume :
4
fYear :
2009
fDate :
8-9 Aug. 2009
Firstpage :
14
Lastpage :
18
Abstract :
To effectively evaluate and predict network security situation, a quantitative model for network security situation awareness based on artificial immune system and grey theory is proposed. In this model, the formal definitions of self, non-self, antigen and detector is given. According to the relationship between the antibody-concentration of memory detector and the attack intensity of network, network security situation evaluation sub-model based on artificial immune system is given. And to forecast the attack intensity that the current network faces in the next step, network situation predication sub-model based on grey theory is given. Experimental results exhibit that the proposed model provides a novel approach for network security situation awareness, and holds better characters of self-adaptability and real-time processing.
Keywords :
artificial immune systems; security of data; self-adjusting systems; artificial immune system; grey theory; network security situation awareness; quantitative model; real-time processing; self-adaptability; Artificial immune systems; Biological system modeling; Computer networks; Computer security; Detectors; Immune system; Information security; Predictive models; Stability; Surveillance; Artificial Immune System; Grey Prediction; Situation Awareness; Situation Evaluation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computing, Communication, Control, and Management, 2009. CCCM 2009. ISECS International Colloquium on
Conference_Location :
Sanya
Print_ISBN :
978-1-4244-4247-8
Type :
conf
DOI :
10.1109/CCCM.2009.5267847
Filename :
5267847
Link To Document :
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