Generative Adversarial Networks for Cybersecurity:: Protecting Data and Networks

Generative Adversarial Networks (GANs) play a crucial dual role in cybersecurity, serving both as powerful defensive tools and sophisticated attack vectors that security professionals must understand and counter.GANs are invaluable for generating synthetic datasets to train cybersecurity models when real attack data is scarce or sensitive, creating realistic network traffic patterns for testing intrusion detection systems, and augmenting threat intelligence by simulating various attack scenarios without exposing actual vulnerabilities. Exploring the application of GAN models in intrusion detection, anomaly detection, and cybercrime, Generative Adversarial Networks for Cybersecurity: Protecting Data and Networks covers how GANs can be applied to pinpoint security holes, vulnerabilities, viruses, malware, phishing attacks, and other security risks.It explains how advanced GANs integrated with such digital technologies as the Internet of Things (IoT), cloud-native computing, edge analytic