Malicious data attack on real-time electricity market

Abstract

Malicious data attacks to the real-time electricity market are studied. In particular, an adversary launches an attack by manipulating data from a set of meters with the goal of influencing revenues of a real-time market. The adversary must deal with the tradeoff between avoiding being detected by the control center and making maximum profit from the real time market. Optimal attacking strategy is obtained through an optimization of a quasi-concave objective function. It is shown that the probability of detection of optimal attack will always be less than 0.5. Attack performance is evaluated using simulations on the IEEE 14-bus system.