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Exploring the Role of Generative Adversarial Networks in Cybersecurity: Techniques, Applications, and Advancements
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Author(s): Ambika S. Jaiswal (Sant Gadge Baba Amravati University, India), Dipak V. Bhavsagar (Seth Kesarimal Porwal College of Arts and Science and Commerce, India), Sonali Ravindra Chavan (Bharatiya Mahavidyalaya, Amravati, India), Priyanka C. Tikekar (Bharatiya Mahavidyalaya, Amravati, India)and Suhashini Chaurasia (S.S. Maniar College of Computer and Management, Nagpur, India)
Copyright: 2024
Pages: 13
Source title:
Enhancing Security in Public Spaces Through Generative Adversarial Networks (GANs)
Source Author(s)/Editor(s): Sivaram Ponnusamy (Sandip University, Nashik, India), Jilali Antari (Ibn Zohr Agadir University, Morocco), Pawan R. Bhaladhare (Sandip University, Nashik, India), Amol D. Potgantwar (Sandip University, Nashik, India)and Swaminathan Kalyanaraman (Anna University, Trichy, India)
DOI: 10.4018/979-8-3693-3597-0.ch017
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Abstract
To protect the vast amounts of data being stored on computers and transported over networks, cybersecurity is crucial. To prevent increasingly complex assaults in the future, methods for identifying threats must be regularly updated. Experts in security are using GAN to accomplish results in password cracking, anomaly generation, and intrusion detection. The creative use of GANs in cybersecurity is explored in this chapter. An overview of GANs and their importance in strengthening cyber defense mechanisms is presented in the introduction. An extensive literature analysis to clarify the current state of knowledge is provided after a detailed examination of traditional GAN techniques. The chapter clarifies the GAN's architectural subtleties and highlights its applicability to cybersecurity scenarios. Additionally, study of variety of GAN applications in cybersecurity. It classifies different kinds of GANs and frameworks used in their application. It studied the intrusion detection-based GAN model with its parameters results compared with the existing study.
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