  Cyber data attacks are the worst-case interacting bad data to power system
state estimation and cannot be detected by existing bad data detectors. In this
paper, we for the first time analyze the likelihood of cyber data attacks by
characterizing the actions of a malicious intruder. We propose to use Markov
decision process to model an intruder's strategy, where the objective is to
maximize the cumulative reward across time. Linear programming method is
employed to find the optimal attack policy from the intruder's perspective.
Numerical experiments are conducted to study the intruder's attack strategy in
test power systems.
