A visualization method of attack path based on network traffic in power system
Zhiyuan Pan, Lisong Shao, Xinxin Song, Wei Wang · International Conference on Artificial Intelligence · 2021
Since the power system can guarantee the stability of the national economy, the security of the power system is particularly important. The attack visualization technology can display network attacks intuitively, and it can help the security personnel to analyze network attacks intuitively. So the visualization research of network attacks in power systems has significance to the internal security analysis of power systems. Aiming at the network attacks in the power system, in this paper, a visualization method of attack path based on the network traffic existing in the power system was studied. The method is divided into four modules: data collection module, generating attacker’s fingerprint database module, reverse tracing module, and attack path visualization module. The method can trace the network attacks of the power system and achieve attack path visualization based on the reverse tracing module. Through the simulation experiments, the proposed method can show the attack path in the power system well.