Explicit Analysis on Effectiveness and Hiddenness of Moving Target Defense in AC Power Systems

Moving target defense (MTD) is becoming promising in thwarting the false data injection attacks (FDIAs) on power system state estimation (SE). However, due to the nonlinear dynamics of AC power systems, the investigation of the general evaluation metrics of MTD, namely the effectiveness in terms of attack detection and the hiddenness, is still challenging. To this end, in this paper, we attempt to conduct an explicit analysis on the MTD performance in AC power systems. First, we derive explicit approximations of measurement residuals to quantify the two metrics. Then, based on the projection matrix, maximizing the effectiveness is transformed to maximizing the lower bound of the approximated residual, under which the matrix inverse issue is addressed. Moreover, the maximization of hiddenness is achieved by the minimization of the approximated power flow difference caused by reactance perturbation. To balance the trade-off between effectiveness and hiddenness, the design of explicit residual-based MTD (EXR-MTD) is accomplished by aggregating the two sub-problems with an appropriate weight. Finally, extensive simulations are conducted to validate the performance of EXR-MTD. Numerical results indicate that EXR-MTD performs better than existing MTD strategies in terms of hiddenness, while the effectiveness of EXR-MTD is comparable to those of existing MTD strategies.

Automated summary

This paper provides an explicit analysis of the performance of moving target defense (MTD) in AC power systems. It derives explicit approximations of measurement residuals to quantify performance metrics and proposes a design method for explicit residual-based MTD (EXR-MTD) to balance effectiveness and hiddenness.