Intrusion detection techniques of variable-frequency vector control system

As induction motors are the control core in variable-frequency speed-regulating systems, their efficient operation in industrial production processes needs to be ensured. To realize this, the accuracy and security of control commands and equipment parameters have been the priorities for industrial security protection research. This study aims to investigate the intrusion detection techniques of the AC-DC-AC variable-frequency vector control system for induction motors under EtherCAT industrial bus. First, the EtherCAT bus protocol is deeply analyzed, and combined with the EtherCAT industrial bus common protocol vulnerabilities that have been discovered so far, the key characteristics of the protocol data packets are extracted, and the EtherCAT bus protocol intrusion detection rule base is constructed. A three-dimensional pointer linked list tree is used as the retrieval data structure for the EtherCAT bus protocol rule base. Second, model parameters are simulated and calculated based on the physical model of the AC-DC-AC inverter vector control system of the induction motor. Then a least-squares support vector machine (LSSVM) with the characteristics of vector control model intrusion is constructed on the basis of the simulation results, and the parameters of LSSVM classifier are optimized using the chaotic particle swarm optimization (CPSO) algorithm, both of which constitute the CPSO-LSSVM intrusion detection classification algorithm. After the anomaly data packets are classified, they will be transferred to the Suricata intrusion detection engine for precise rule matching. Finally, a physical experiment environment is built for the intrusion detection system. The simulation results of the AC-DC-AC variable-frequency vector control model in this paper show good dynamic performance, which is similar to the trend of waveform change on actual vector control system parameters. The effectiveness of the intrusion detection system is verified by extracting part of the KDD Cup99 test dataset to implement the behaviors of attacks, such as the denial of service (DOS), remote-to-local (R2L), user-to-root (U2R), and Probing attacks on the intrusion detection system.