A Comprehensive Study of Generative Adversarial Networks (GAN) and Generative Pre-Trained Transformers (GPT) in Cybersecurity

The evolution of Generative Artificial Intelligence (GAI) is the main highlight of digital transformation in year 2022. With the progression of GAI techniques; Generative Adversarial Networks (GAN) and Generative Pre-trained transformers (GPT), it became significantly crucial to understand the consequences of using these techniques in the cybersecurity domain. Several researchers are demonstrating the use of GAI techniques in the field of cybersecurity from both the defensive and offensive point of view. This research paper highlights the opportunities, limitations and the potential risks associated with GAN and GPT in the world of cybersecurity. The work represents how the incorporation of GAN and GPT technologies strengthens the security system by identifying, preventing and defending the cyberattacks. Hence, offering both innovative solutions and new challenges. This paper also examines how cyber offenders can misuse the GAI tools in developing cyberattacks by studying the conditions where GAN, GPT can be used by adversaries to create self-evolving malware, phishing attacks, automated hacking etc. This paper also observes the defense procedures using GAI tools to enhance security measures, detect cyber threats, create strong defense mechanisms, malware detection and classification and adversarial attack simulation. By outlining the prospect of GAI applications and pointing toward future directions, this work emphasizes open challenges and serves as a valuable resource for both the research community and industry practitioners, highlighting the critical need for continued innovation and evaluation in exploiting GAIs to reinforce cybersecurity defenses.