Visible to the public Modeling Cyber Resilience for Energy Delivery Systems Using Critical System Functionality

TitleModeling Cyber Resilience for Energy Delivery Systems Using Critical System Functionality
Publication TypeConference Paper
Year of Publication2019
AuthorsHaque, Md Ariful, Shetty, Sachin, Krishnappa, Bheshaj
Conference Name2019 Resilience Week (RWS)
Date Publishednov
KeywordsAHP, analytic hierarchy process, analytical hierarchy process, Computing Theory, Control Theory and Resiliency, critical cyber components, critical system functionality, CSF, cyber resilience, EDS map, energy delivery systems, graph Laplacian matrix, graph theory, matrix algebra, pubcrawl, resilience, Resiliency, safety-critical software, security of data, system recovery curve, TOPSIS, Vulnerability Graph, vulnerability graph representation

In this paper, we analyze the cyber resilience for the energy delivery systems (EDS) using critical system functionality (CSF). Some research works focus on identification of critical cyber components and services to address the resiliency for the EDS. Analysis based on the devices and services excluding the system behavior during an adverse event would provide partial analysis of cyber resilience. To address the gap, in this work, we utilize the vulnerability graph representation of EDS to compute the system functionality under adverse condition. We use network criticality metric to determine CSF. We estimate the criticality metric using graph Laplacian matrix and network performance after removing links (i.e., disabling control functions, or services). We model the resilience of the EDS using CSF, and system recovery curve. We also provide a comprehensive analysis of cyber resilience by determining the critical devices using TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) and AHP (Analytical Hierarchy Process) methods. We present use cases of EDS illustrating the way control functions and services in EDS map to the vulnerability graph model. The simulation results show that we can estimate the resilience metric using different types of graphs that may assist in making an informed decision about EDS resilience.

Citation Keyhaque_modeling_2019