A GAN-Based False Data Injection and Civil Attack Detection Framework for Digital Relays with Feature Selection

As one of the highly used components in the power system, digital relays are employed to use the phasor measurement units', voltage, and current signals, to decide whether a fault has occurred in the system or not. The major difference between digital relays and traditional ones is that the former receives the mentioned signals mostly by wireless communication paths, instead of using measurement transformers. While the wireless signals used as the input of digital relays are vulnerable to cyber-attacks, a proper cybersecurity solution for digital relays is demanding. Due to the pervasive use of AI-based techniques in cybersecurity, one of the most vital features of a cybersecurity method is its training data volume. Hence, we employed a modified generative adversarial network that is able to generate attacked data by itself, meaning that there is no need to train the neural network with the cyber-attacked data. Additionally, a feature selection method called extra tree classifier is used to reduce the dimension of our input data. The discriminator sector of the generative adversarial network is then used as the classifier to detect false data injection, civil attacks, and faults which is preventing the digital relay from tripping falsely. The two mentioned cyber-attacks, false data injection and civil-attack, are used to evaluate the performance of our proposed method in 29 different scenarios. The IEEE 39-bus transmission network is employed as our test system. The proposed cyber-attack detection method was able to classify the faults and mentioned cyber-attacks in most scenarios with more than 97 percent of accuracy, f1 score, and more than 96 percent of sensitivity. We also examined the proposed modified GAN-based method by giving it only the voltage signal as input for training, and the method scored at least 90 percent of accuracy, 87 percent of sensitivity, and 88 percent of f1 score in harsh scenarios which is almost as accurately as before when both voltage and current signals were used for the relay as inputs, making the proposed technique universal and suitable for other types of relays.