A Sponsor Incentive Attack Scheme for Feeder Automation Systems

Abstract

The rapid deployment of intelligent electronic devices and the development of information and communication technology have improved distribution network (DN) reliability with feeder automation. Thus, the operation of DNs has become more dependent on the cyber-physical components. As the cyber security of smart grid has drawn increasing attention in recent years, this paper proposes a simple yet powerful type of attack targeting the remote terminal units. The proposed attack policy can manipulate the feeder automation operation with the aim of cutting off important power consumers. Regarding the realistic cyber-attacks that previously occurred, an optimal attack model is established for analyzing the attack policy. This optimization model aims to minimize the attack cost and the penalty of being caught or detected while maximizing the remuneration. A Bayesian attack graph model is adopted to quantify the successful probability of exploiting known and zero-day vulnerabilities. The probability of a cyber-attack being caught or detected is modeled based on search theory. Next, an enhanced self-adaptive evolutionary programming is developed to achieve satisfactory solutions for practical applications. Finally, the proposed model and corresponding solution strategies are verified using the RBTS bus 2 DN and the modified IEEE 123-node test feeder.