Smart Grid Security: Threats, Challenges, and Solutions

The cyber-physical nature of the smart grid has rendered it vulnerable to a multitude of attacks that can occur at its communication, networking, and physical entry points. Such cyber-physical attacks can have detrimental effects on the operation of the grid as exemplified by the recent attack which caused a blackout of the Ukranian power grid. Thus, to properly secure the smart grid, it is of utmost importance to: a) understand its underlying vulnerabilities and associated threats, b) quantify their effects, and c) devise appropriate security solutions. In this paper, the key threats targeting the smart grid are first exposed while assessing their effects on the operation and stability of the grid. Then, the challenges involved in understanding these attacks and devising defense strategies against them are identified. Potential solution approaches that can help mitigate these threats are then discussed. Last, a number of mathematical tools that can help in analyzing and implementing security solutions are introduced. As such, this paper will provide the first comprehensive overview on smart grid security

Secure Distributed Dynamic State Estimation in Wide-Area Smart Grids

Smart grid is a large complex network with a myriad of vulnerabilities, usually operated in adversarial settings and regulated based on estimated system states. In this study, we propose a novel highly secure distributed dynamic state estimation mechanism for wide-area (multi-area) smart grids, composed of geographically separated subregions, each supervised by a local control center. We firstly propose a distributed state estimator assuming regular system operation, that achieves near-optimal performance based on the local Kalman filters and with the exchange of necessary information between local centers. To enhance the security, we further propose to (i) protect the network database and the network communication channels against attacks and data manipulations via a blockchain (BC)-based system design, where the BC operates on the peer-to-peer network of local centers, (ii) locally detect the measurement anomalies in real-time to eliminate their effects on the state estimation process, and (iii) detect misbehaving (hacked/faulty) local centers in real-time via a distributed trust management scheme over the network. We provide theoretical guarantees regarding the false alarm rates of the proposed detection schemes, where the false alarms can be easily controlled. Numerical studies illustrate that the proposed mechanism offers reliable state estimation under regular system operation, timely and accurate detection of anomalies, and good state recovery performance in case of anomalies

Subspace Methods for Data Attack on State Estimation: A Data Driven Approach

Data attacks on state estimation modify part of system measurements such that the tempered measurements cause incorrect system state estimates. Attack techniques proposed in the literature often require detailed knowledge of system parameters. Such information is difficult to acquire in practice. The subspace methods presented in this paper, on the other hand, learn the system operating subspace from measurements and launch attacks accordingly. Conditions for the existence of an unobservable subspace attack are obtained under the full and partial measurement models. Using the estimated system subspace, two attack strategies are presented. The first strategy aims to affect the system state directly by hiding the attack vector in the system subspace. The second strategy misleads the bad data detection mechanism so that data not under attack are removed. Performance of these attacks are evaluated using the IEEE 14-bus network and the IEEE 118-bus network.Comment: 12 page