Logo image
On Effectiveness of Detecting FDI Attacks on Power Grid using Moving Target Defense
Conference proceeding

On Effectiveness of Detecting FDI Attacks on Power Grid using Moving Target Defense

Zhenyong Zhang, Ruilong Deng, David Yau, Peng Cheng, Jiming Chen and IEEE
Innovative Smart Grid Technologies, pp.1-5
Innovative Smart Grid Technologies
01/01/2019

Abstract

Computer Science Computer Science, Interdisciplinary Applications Engineering Engineering, Electrical & Electronic Science & Technology Technology
Recent studies have considered thwarting false data injection (FDI) attacks against state estimation in a power grid by proactively perturbing branch susceptances. The approach is known as moving target defense (MTD). However, the effectiveness of MTD has not been thoroughly analyzed in the existing literature. In this paper, we prove that, despite of the deployment of MTD, it is possible for the attacker to launch stealthy FDI attacks if the number of branches l of the power system is less than twice the number of system states n (i.e., l < 2n, where n + 1 is the number of buses) based on the DC power flow model. Moreover, MTD has the complete capability to detect any FDI attacks with the form a = H c only if the susceptances of more than n branches, which cover all buses, are perturbed. In addition, we analyze the impact of the susceptance perturbations on the attack space. We illustrate our findings on an IEEE test power system using load traces from the state of New York.

Metrics

1 Record Views

Details

Logo image