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dc.contributor.authorTerziyan, Vagan
dc.contributor.authorGryshko, Svitlana
dc.contributor.authorGolovianko, Mariia
dc.contributor.editorLongo, Francesco
dc.contributor.editorAffenzeller, Michael
dc.contributor.editorPadovano, Antonio
dc.date.accessioned2021-02-23T13:27:18Z
dc.date.available2021-02-23T13:27:18Z
dc.date.issued2021
dc.identifier.citationTerziyan, 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.), <i>ISM 2020 : Proceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing</i> (180, pp. 676-685). Elsevier. Procedia Computer Science. <a href="https://doi.org/10.1016/j.procs.2021.01.290" target="_blank">https://doi.org/10.1016/j.procs.2021.01.290</a>
dc.identifier.otherCONVID_51610660
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/74366
dc.description.abstractIndustry 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.pptxen
dc.format.extent1058
dc.format.mimetypeapplication/pdf
dc.languageeng
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofISM 2020 : Proceedings of the 2nd International Conference on Industry 4.0 and Smart Manufacturing
dc.relation.ispartofseriesProcedia Computer Science
dc.rightsCC BY-NC-ND 4.0
dc.subject.otherIndustry 4.0
dc.subject.otherGenerative Adversarial Networks
dc.subject.othercybersecurity
dc.subject.otherartificial digital immunity
dc.titleTaxonomy of generative adversarial networks for digital immunity of Industry 4.0 systems
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-202102231752
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.type.coarhttp://purl.org/coar/resource_type/c_5794
dc.description.reviewstatuspeerReviewed
dc.format.pagerange676-685
dc.relation.issn1877-0509
dc.relation.volume180
dc.type.versionpublishedVersion
dc.rights.copyright© 2021 the Authors
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational Conference on Industry 4.0 and Smart Manufacturing
dc.subject.ysoneuroverkot
dc.subject.ysoälytekniikka
dc.subject.ysokyberturvallisuus
dc.subject.ysokoneoppiminen
dc.subject.ysoesineiden internet
dc.subject.ysotekoäly
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p7292
jyx.subject.urihttp://www.yso.fi/onto/yso/p27260
jyx.subject.urihttp://www.yso.fi/onto/yso/p26189
jyx.subject.urihttp://www.yso.fi/onto/yso/p21846
jyx.subject.urihttp://www.yso.fi/onto/yso/p27206
jyx.subject.urihttp://www.yso.fi/onto/yso/p2616
dc.rights.urlhttps://creativecommons.org/licenses/by-nc-nd/4.0/
dc.relation.doi10.1016/j.procs.2021.01.290
dc.type.okmA4


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