  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.
