A4 Article in conference proceedings
Taxonomy of generative adversarial networks for digital immunity of Industry 4.0 systems (2021)


Terziyan, V., Gryshko, S., & Golovianko, M. (2021). Taxonomy of generative adversarial networks for digital immunity of Industry 4.0 systems. In F. Longo, M. Affenzeller, & A. Padovano (Eds.), ISM 2020 : Proceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing (180, pp. 676-685). Elsevier. Procedia Computer Science. https://doi.org/10.1016/j.procs.2021.01.290


JYU authors or editors


Publication details

All authors or editors: Terziyan, Vagan; Gryshko, Svitlana; Golovianko, Mariia

Parent publication: ISM 2020 : Proceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing

Parent publication editors: Longo, Francesco; Affenzeller, Michael; Padovano, Antonio

Conference:

  • International Conference on Industry 4.0 and Smart Manufacturing

Place and date of conference: Virtual Online Conference, 23.-25.11.2020

Journal or series: Procedia Computer Science

eISSN: 1877-0509

Publication year: 2021

Volume: 180

Pages range: 676-685

Number of pages in the book: 1058

Publisher: Elsevier

Publication country: Netherlands

Publication language: English

DOI: https://doi.org/10.1016/j.procs.2021.01.290

Publication open access: Openly available

Publication channel open access: Open Access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/74366


Abstract

Industry 4.0 systems are extensively using artificial intelligence (AI) to enable smartness, automation and flexibility within variety of processes. Due to the importance of the systems, they are potential targets for attackers trying to take control over the critical processes. Attackers use various vulnerabilities of such systems including specific vulnerabilities of AI components. It is important to make sure that inappropriate adversarial content will not break the security walls and will not harm the decision logic of critical systems. We believe that the corresponding security toolse must be organized as a trainable self-protection mechanism similar to immunity. We found certain similarities between digital vs. biological immunity and we study the possibilities of Generative Adversarial Networks (GANs) to provide the basis for the digital immunity training. We suggest the taxonomy of GANs (including new architectures) suitable to simulate various aspects of the immunity for Industry 4.0 applications.
See presentation slides: https://ai.it.jyu.fi/ISM-2020-GAN-Taxonomy.pptx


Keywords: Internet of things; intelligent systems; artificial intelligence; cyber security; machine learning; neural networks (information technology)

Free keywords: Industry 4.0; Generative Adversarial Networks; cybersecurity; artificial digital immunity


Contributing organizations


Ministry reporting: Yes

Reporting Year: 2021

JUFO rating: 1


Last updated on 2024-22-04 at 14:49