Abstract: The power grid state estimation (SE) has been shown to be vulnerable to false data injection (FDI) attacks, which can lead to severe consequences, e.g., transmission line trips, unsafe frequency excursions and/or economic losses. In this talk, we will examine the security of power gird SE from both the attacker and the defender’s perspective. For the former, we examine data-driven FDI attacks, i.e., constructing FDI attacks that can bypass the grid’s bad-data detector (BDD) by accessing its measurement data over a period of time. We characterize important tradeoffs for the attacker in this context between the attack’s spatial and temporal efficiency. The results provide us with an important understanding for designing defense mechanism to thwart such attacks.
For defense, we propose a hardened-attack detector based on moving-target defense (MTD) that actively perturbs transmission line reactances to invalidate the attacker’s knowledge. We present novel formal design criteria to select MTD reactance perturbations that are truly effective. Moreover, based on a key optimal power flow formulation, we find that the effective MTD may incur a non-trivial operational cost that has not hitherto received attention. Accordingly, we characterize important tradeoffs between the MTD’s detection capability and its associated required cost. Extensive simulations, using the MATPOWER simulator and benchmark IEEE bus systems, verify and illustrate the proposed design approach.
Bio: Subhash Lakshminarayana is a researcher working at the Advanced Digital Sciences Center (ADSC), a research laboratory established by the University of Illinois, Urbana Champaign in Singapore.
His research interests include cyber-physical systems security and control and wireless communications. His works have been selected among the Best Conference Papers on integration of renewable and intermittent resources at the IEEE Power Energy Society General Meeting (PESGM) 2015 conference, and the Best 50 Papers at the IEEE Globecom 2014 conference. More information on his research can be found at: https://sites.google.com/site/subhashlakshminarayana/