<p>Electrical industrial enterprises are an important part of the national economy, and the network security of their industrial control systems is particularly important. In recent years, software-defined network has been widely used in electrical industrial control systems due to its advantages such as cost reduction and system security enhancement. A hybrid algorithm based on enhanced cuckoo and support vector machine is suggested to address the issues of low accuracy and low efficiency of the currently used software-defined network intrusion detection methods for electrical industrial control systems. Additionally, the hybrid algorithm is used to build the intrusion detection model of the electrical industrial control system network by the application of the hybrid algorithm. Experiments comparing the hybrid algorithm’s performance to that of other algorithms were conducted. It was discovered that the hybrid algorithm outperformed the comparative algorithms by a large margin, with average accuracy and precision of 96.9 and 98.6%, respectively. Simulation tests of distributed denial of service attacks were then conducted on the detection model. The outcomes indicated that the detection success rate and false detection rate of the proposed detection model were 95.1 and 1.3%, respectively, which were better compared to the comparison model. The above results demonstrate that the proposed hybrid algorithm and detection model are effective. They provide a theoretical basis for network security defense in industrial control systems and guarantee the safety of their operations.</p>