Abstract: The two-tier cybersecurity method applies malware detection to a network. The malware detection is based on a generative adversarial network (GAN). Additionally, each user accesses the network through a privacy-preserving interface which applies a federated learning-based data-sharing model. Known malicious and known benign files are converted into corresponding images, and these corresponding images are used as input sample data for the generative adversarial network for generating a class vector for classifying and identifying malware. A malware detector uses the class vector output by the GAN for malware identification. Additionally, a privacy-preserving interface is established for each user of the network. The privacy-preserving interface is a federated learning-based data-sharing model.