The IRMA Community
Newsletters
Research IRM
Click a keyword to search titles using our InfoSci-OnDemand powered search:
|
Overview of Generative AI Techniques for Cybersecurity
|
|
Author(s): Siva Raja Sindiramutty (Taylor's University, Malaysia), Krishna Raj V. Prabagaran (Universiti Malaysia Sarawak, Malaysia), Rehan Akbar (Florida International University, USA), Manzoor Hussain (Indus University, Pakistan)and Nazir Ahmed Malik (Bahria University, Islamabad, Pakistan)
Copyright: 2025
Pages: 52
Source title:
Reshaping CyberSecurity With Generative AI Techniques
Source Author(s)/Editor(s): Noor Zaman Jhanjhi (School of Computing Science, Taylor's University, Malaysia)
DOI: 10.4018/979-8-3693-5415-5.ch001
Purchase
|
Abstract
Generative AI techniques have been popular since they can generate data or content that could be hardly distinguished from genuine ones. This chapter comprehensively reviews generative AI for cybersecurity and its definition, history, and applications in different fields. It covers basic ideas such as generative models, probability distributions, and latent spaces. Also, it goes into more detail on some of the more popular approaches like GANs, VAEs, and the combination of RL. The chapter explores the structure and training processes of GANs and VAEs and demonstrates their application in tasks such as image synthesis, data enhancement, and novelty detection. Also, it explores the interaction between RL and generative models and the challenges, including the exploration-exploitation trade-off. The chapter focuses on the development of generative AI with the help of DL and analyses the benefits of deep generative models and their usage in various fields. Evaluation measures and the problems with measuring generative models are discussed, focusing on the methods of improving the measurement accuracy. Finally, the chapter focuses on new directions, like transformer-based models and self-supervised learning, to look at the future of generative AI. The emphasis is made on understanding these techniques due to their versatility, and some ideas about the possible further developments of the findings for other fields and future studies and applications are provided.
Related Content
|
Frederic Andres.
© 2027.
14 pages.
|
|
Kalsoom Safdar, Khairul Najmy Abdul Rani, Mohd Aminudin Jamlos, Siti Julia Rosli, Muhammad Usman Younus, Zanab Safdar.
© 2027.
27 pages.
|
|
Bani Adam, Binastya Anggara Sekti, Muhammad Adi Zacky Zahran.
© 2027.
24 pages.
|
|
Swetha Margaret T. A., Renuka Devi D..
© 2027.
31 pages.
|
|
Maurice Saluschke, Michael Schulz.
© 2027.
30 pages.
|
|
Mirjam Sepesy Maučec, Gregor Donaj.
© 2027.
16 pages.
|
|
Jorge A. Ruiz-Vanoye, Ocotlan Diaz-Parra, Ricardo A. Barrera-Cámara, Alejandro Fuentes-Penna, Francisco R. Trejo-Macotela, Jaime Aguilar-Ortiz, Eric Simancas-Acevedo.
© 2027.
21 pages.
|
|
|