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Graph-Theoretic Framework for Unified Analysis of Observability and Data Injection Attacks in the Smart Grid

In this paper, a novel graph-theoretic framework is proposed to generalize the analysis of a broad set of security attacks, including observability and data injection attacks, that target the state estimator of a smart grid. First, the notion of observability attacks is defined based on a proposed graph-theoretic construct. In this respect, a structured approach is proposed to characterize critical sets, whose removal renders the system unobservable. It is then shown that, for the system to be observable, these critical sets must be part of a maximum matching over a proposed bipartite graph. In addition, it is shown that stealthy data injection attacks (SDIAs) constitute a special case of these observability attacks. Then, various attack strategies and defense policies, for observability and data injection attacks, are shown to be amenable to analysis using the introduced graph-theoretic framework. The proposed framework is then shown to provide a unified basis for analysis of four key security problems (among others), pertaining to the characterization of: 1) The sparsest SDIA; 2) the sparsest SDIA including a certain measurement; 3) a set of measurements which must be defended to thwart all potential SDIAs; and 4) the set of measurements, which when protected, can thwart any SDIA whose cardinality is below a certain threshold. A case study using the IEEE 14-bus system with a set of 17 measurements is used to support the theoretical findings.

preprint2020arXivOpen access
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