A Prediction Method of Network Security Situation

Author

Wan Ziqian ; Li Tao ; Liang Gang

Author_Institution

Sch. of Comput. Sci., Sichuan Univ., Chengdu, China

fYear

2009

fDate

20-22 Sept. 2009

Firstpage

1

Lastpage

4

Abstract

A prediction method of network security situation based on gen expression programming (PCN_GEP) has been proposed. The main contribution include: (1) Propose cycle-weighted sliding window prediction method to deal with the cycle-changing network risk situation. (2) Fibonacci-weight is added to the preprocess of training dataset to ensure that the latest data have the most impaction to the future. Immunity model which can dynamically reflect the network real-time state has been introduced into computer network risk evaluation to get the initial training data in our experimentation, the experimentation results proved that this method has high precision in the forecasting of computer network security situation.

Keywords

genetic algorithms; risk analysis; security of data; Fibonacci-weight preprocesses; artificial immunity system; computer network risk evaluation; computer network security situation forecasting; cycle-weighted sliding window prediction method; dataset training preprocessing; genes expression programming; immunity model; network risk situation; Biological cells; Computer networks; Computer science; Computer security; Data security; Information security; Prediction methods; Predictive models; Random number generation; Training data;

fLanguage

English

Publisher

ieee

Conference_Titel

Management and Service Science, 2009. MASS '09. International Conference on

Conference_Location

Wuhan

Print_ISBN

978-1-4244-4638-4

Electronic_ISBN

978-1-4244-4639-1

Type

conf

DOI

10.1109/ICMSS.2009.5301216

Filename

5301216