Efficient Computations of a Security Index for False Data Attacks in Power Networks

TL;DR

This paper presents efficient algorithms for computing a security index to assess the vulnerability of power network measurement systems to false data attacks, including exact solutions under full measurement and heuristic methods for general cases.

Contribution

It introduces the first exact polynomial-time algorithm for vulnerability analysis in full measurement scenarios and heuristic algorithms for the general NP-hard problem.

Findings

Exact algorithm for full measurement case

Heuristic algorithm for general NP-hard case

Numerical validation on IEEE 118-bus system

Abstract

The resilience of Supervisory Control and Data Acquisition (SCADA) systems for electric power networks for certain cyber-attacks is considered. We analyze the vulnerability of the measurement system to false data attack on communicated measurements. The vulnerability analysis problem is shown to be NP-hard, meaning that unless $P = NP$ there is no polynomial time algorithm to analyze the vulnerability of the system. Nevertheless, we identify situations, such as the full measurement case, where it can be solved efficiently. In such cases, we show indeed that the problem can be cast as a generalization of the minimum cut problem involving costly nodes. We further show that it can be reformulated as a standard minimum cut problem (without costly nodes) on a modified graph of proportional size. An important consequence of this result is that our approach provides the first exact efficient algorithm for the vulnerability analysis problem under the full measurement assumption. Furthermore, our approach also provides an efficient heuristic algorithm for the general NP-hard problem. Our results are illustrated by numerical studies on benchmark systems including the IEEE 118-bus system.