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Content available remote BAGS: a tool to quantify smart grid resilience
EN
In this paper, we present the Bayesian Attack Graph for Smart Grid (BAGS) tool to quantify smart grid resilience in the presence of multiple cyber-physical attacks. BAGS takes system functions, network architecture, applications and a vulnerability report as input and generates three Bayesian Networks at three different levels of hierarchy. The top level network is called Functional Bayesian Network that defines how smart grid functions are connected. System engineers can select a particular function on a dashboard and view the Network Bayesian Network of that function at the second level. They can also choose a particular network component to see the list of vulnerabilities and the probability of associated compromise at the third level. System engineers can incorporate this functionality into their system and analyze the impact of any compromised component of the smart grid system on its resilience. Furthermore, BAGS helps to identify the failure paths in advance from one power grid function to another so that they can devise secure strategies and deploy resources effectively and efficiently.
EN
Development Of Electrical Power Systems And Their Integration With An Increasing Number Of Smart Automation Devices Compel To Undertake A New Approach To The Issue Of The System’s Security. Reliability Of An Electrical Power System And High Service Availability Are The Essential Characteristics Of Efficient Strategic Electricity Customers, I.E.: Large Industrial Facilities, Railway Transport, Medical Service Providers And Life-Saving Institutions. The Time Of Manual Or Automatic System Recovery After A Failure, Which Increases Its Security, Is Not Without Significance, Either. The Article Discusses The Issues Of Risk Assessment And Management, Including The Overall Process Of Analysis And Assessment Of Threat Probability In Electrical Power Systems.
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