Title :
The Research on Dynamic Risk Assessment Based on Hidden Markov Models
Author :
Cheng, Xiaorong ; Ni, Yangdan
Author_Institution :
Sch. of Control & Comput. Eng., North China Electr. Power Univ., Baoding, China
Abstract :
In order to effectively finish the dynamic risk assessment of the electricity system, this paper will divide each attack into three distinct phases, The difficulty of attack is assessed by percent of each attack time of distinct stages take up in the total attack time to describe the attack difficulty in order to determine the status of the assets transition matrix, realising the dynamic nature of risk assessment. The real-time dynamic risk assessment methods based on Hidden Markov Model HMM has a strong adaptability and scalability, it can be effectively applied on the network, host, system, service level of risk assessment. This paper designs and implements the dynamic risk assessment examples power system, and then demonstrateds the dynamic assessment model.
Keywords :
hidden Markov models; matrix algebra; power engineering computing; power system security; risk management; security of data; adaptability; assets transition matrix; electricity system; hidden Markov model; power system; real-time dynamic risk assessment method; risk assessment service level; scalability; total attack time; Heuristic algorithms; Hidden Markov models; Markov processes; Power system dynamics; Risk management; Security; Vectors; Hidden Markov; data integration; dynamic risk assessment; neural networks;
Conference_Titel :
Computer Science & Service System (CSSS), 2012 International Conference on
Conference_Location :
Nanjing
Print_ISBN :
978-1-4673-0721-5
DOI :
10.1109/CSSS.2012.280