LAUSR

To warn the cascading failures caused by cyberattacks (CFCAs) in real time and reduce their damage on cyber-physical power systems (CPPSs), a novel early warning method based on attack gains and cost principle (AGCP) is proposed. Firstly, according to the CFCA characteristics, the leading role of attackers in the whole evolutionary process is discussed. The breaking out of a CFCA is deduced based on the AGCP from the view of attackers, and the priority order of all CFCAs is then provided. Then, the method to calculate the probability of CFCAs is proposed, and an early warning model for CFCA is designed. Finally, to verify the effectiveness of this method, a variety of CFCAs are simulated in a local CPPS model based on the IEEE 39-bus system. The experimental results demonstrate that this method can be used as a reliable assistant analysis technology to facilitate early warning of CFCAs.