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