Unleashing the Power of Generative Adversarial Networks for Cybersecurity: Proactive Defense and Innovation

Abstract

In the cybersecurity arena, generative adversarial networks, or GANs, are a potent technique that has gained attention. Examining GANs' potential in domains such as malware analysis, adversarial defence, and anomaly detection, this book chapter explores the use of GANs to bolster defences against cyberattacks. Cybersecurity experts may create strong detection systems, strengthen their defences against emerging cyber threats, and obtain insights into new attack pathways by utilising GANs' capacity to produce realistic synthetic data and model complex distributions. The theoretical underpinnings of GANs, their architectural modifications, and their practical applications in cybersecurity situations are all thoroughly covered in this chapter. Readers will obtain a thorough grasp of how GANs work through case studies and useful examples from the real world.