Computing is still under a significant threat from ransomware, which necessitates prompt action to prevent it. Ransomware attacks can have a negative impact on how smart grids, particularly digital substations. In addition to examining a ransomware detection method using artificial intelligence (AI), this paper offers a ransomware attack modeling technique that targets the disrupted operation of a digital substation. The first, binary data is transformed into image data and fed into the convolution neural network model using federated learning. The experimental findings demonstrate that the suggested technique detects ransomware with a high accuracy rate.

翻译：计算领域仍面临勒索软件的严重威胁，亟需采取及时措施加以防范。勒索软件攻击可能对智能电网，特别是数字变电站，产生负面影响。本文在探讨基于人工智能（AI）的勒索软件检测方法的同时，提出了一种针对数字变电站运行中断的勒索软件攻击建模技术。首先，将二进制数据转换为图像数据，并通过联邦学习输入卷积神经网络模型。实验结果表明，该方法能够以高准确率检测勒索软件。