A New Information Security Risk Assessment Method in Power Production System Based on Rough Sets and Bayesian Network

Author

Zhonghua Dai ; Haihui Gao ; Yong Peng ; Lu Huikang

Author_Institution

CNITSEC, Beijing, China

fYear

2014

fDate

27-29 Aug. 2014

Firstpage

532

Lastpage

536

Abstract

Power production control system is very important in the power system. In paper, a new method of risk assessment for power system based on rough set theory, fuzzy mathematics and Bayesian network(BN) is presented. Though fuzzy cluster the influencing factors of risk by using compatibles fuzzy rough set, making the minimum risk feature class as a BN node, which can effectively reduce the complexity of the BN structure, At the same time, carry on probabilistic reasoning by using BN, achieve a rapid assessment of risk, then through Anti-fuzzification, obtain the exact value of risks. Finally, examples prove that this method is practicality and effectiveness.

Keywords

belief networks; electricity supply industry; fuzzy set theory; inference mechanisms; power engineering computing; risk management; rough set theory; BN structure; Bayesian network; antifuzzification; fuzzy mathematics; information security risk assessment method; power production system; probabilistic reasoning; rough set theory; Bayes methods; Information security; Power systems; Production control; Risk management; Rough sets; Bayesian Network; control system; power industry; risk assessment; rough set;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP), 2014 Tenth International Conference on

Conference_Location

Kitakyushu

Print_ISBN

978-1-4799-5389-9

Type

conf

DOI

10.1109/IIH-MSP.2014.138

Filename

6998384