DocumentCode :
140318
Title :
Cyber-related risk assessment and critical asset identification in power grids
Author :
Farzan, Farnaz ; Jafari, Mohsen A. ; Wei, Dennis ; Lu, Yang
Author_Institution :
DNV GL-Energy, Chalfont, PA, USA
fYear :
2014
fDate :
19-22 Feb. 2014
Firstpage :
1
Lastpage :
5
Abstract :
This paper proposes a methodology to assess cyber-related risks and to identify critical assets both at power grid and substation levels. The methodology is based on a two-pass engine model. The first pass engine is developed to identify the most critical substation(s) in a power grid. A mixture of Analytical hierarchy process (AHP) and (N-1) contingent analysis is used to calculate risks. The second pass engine is developed to identify risky assets within a substation and improve the vulnerability of a substation against the intrusion and malicious acts of cyber hackers. The risk methodology uniquely combines asset reliability, vulnerability and costs of attack into a risk index. A methodology is also presented to improve the overall security of a substation by optimally placing security agent(s) on the automation system.
Keywords :
analytic hierarchy process; power grids; power system reliability; power system security; risk analysis; substation automation; AHP; N-1 contingent analysis; analytical hierarchy process; asset reliability; automation system; cost vulnerability; critical asset identification; critical substation identification; cyber hackers; cyber related risk assessment; intrusion detection; malicious; optimal placing security; power grid; risk index; risk methodology; second pass engine; substation level; substation vulnerability; two-pass engine model; Automation; Indexes; Modeling; Power grids; Reliability; Security; Substations; cyber security; cyber vulnerability; electrical power grids; risk assessment; substation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Innovative Smart Grid Technologies Conference (ISGT), 2014 IEEE PES
Conference_Location :
Washington, DC
Type :
conf
DOI :
10.1109/ISGT.2014.6816371
Filename :
6816371
Link To Document :
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