Attenuating the Impact of Integrity Attacks on Real-Time Pricing in Smart Grids

TL;DR

This paper investigates the vulnerability of real-time electricity pricing in smart grids to false data injection attacks, proposing new countermeasures to mitigate their impact using advanced analysis and control techniques.

Contribution

It extends prior work by modeling a more powerful adversary, introducing a sensitivity-based analysis method, and proposing multiple countermeasures for attack mitigation.

Findings

Countermeasures like low-pass filtering and anomaly detection reduce attack impact.

Sensitivity functions help analyze the system's vulnerability.

Robust control algorithms improve system resilience.

Abstract

The vulnerability of false data injection attacks on real-time electricity pricing for the power grid market has been recently explored. Previous work has focused on the impact caused by attackers that compromise pricing signals and send false prices to a subset of consumers. In this paper we extend previous work by considering a more powerful and general adversary model, a new analysis method based on sensitivity functions, and by proposing several countermeasures that can mitigate the negative impact of these attacks. Countermeasures include adding a low-pass filter to the pricing signals, selecting the time interval between price updates, selecting parameters of the controller, designing robust control algorithms, and by detecting anomalies in the behavior of the system.