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dc.contributor.authorVähäkainu, Petri
dc.contributor.authorLehto, Martti
dc.contributor.authorKariluoto, Antti
dc.contributor.authorOjalainen, Anniina
dc.contributor.editorJahankhani, Hamid
dc.contributor.editorKendzierskyj, Stefan
dc.contributor.editorChelvachandran, Nishan
dc.contributor.editorIbarra, Jaime
dc.date.accessioned2021-11-30T06:19:28Z
dc.date.available2021-11-30T06:19:28Z
dc.date.issued2020
dc.identifier.citationVähäkainu, P., Lehto, M., Kariluoto, A., & Ojalainen, A. (2020). Artificial Intelligence in Protecting Smart Building’s Cloud Service Infrastructure from Cyberattacks. In H. Jahankhani, S. Kendzierskyj, N. Chelvachandran, & J. Ibarra (Eds.), <i>Cyber Defence in the Age of AI, Smart Societies and Augmented Humanity</i> (pp. 289-315). Springer. Advanced Sciences and Technologies for Security Applications. <a href="https://doi.org/10.1007/978-3-030-35746-7_14" target="_blank">https://doi.org/10.1007/978-3-030-35746-7_14</a>
dc.identifier.otherCONVID_35182733
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/78825
dc.description.abstractGathering and utilizing stored data is gaining popularity and has become a crucial component of smart building infrastructure. The data collected can be stored, for example, into private, public, or hybrid cloud service infrastructure or distributed service by utilizing data platforms. The stored data can be used when implementing services, such as building automation (BAS). Cloud services, IoT sensors, and data platforms can face several kinds of cybersecurity attack vectors such as adversarial, AI-based, DoS/DDoS, insider attacks. If a perpetrator can penetrate the defenses of a data platform, she can cause significant harm to the system. For example, the perpetrator can disrupt a building’s automatic heating system or break the heating equipment by using a suitable attack vector for a data platform. This chapter focuses on examining possibilities to protect cloud storage or data platforms from incoming cyberattacks by using, for instance, artificial-intelligence-based tools or trained neural networks that can detect and prevent typical attack vectors.en
dc.format.extent450
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofCyber Defence in the Age of AI, Smart Societies and Augmented Humanity
dc.relation.ispartofseriesAdvanced Sciences and Technologies for Security Applications
dc.rightsIn Copyright
dc.subject.otherartificial-intelligence-based applications
dc.subject.otherartificial intelligence
dc.subject.othercloud service
dc.subject.otherdata platform
dc.subject.otherattack vectors
dc.titleArtificial Intelligence in Protecting Smart Building’s Cloud Service Infrastructure from Cyberattacks
dc.typebookPart
dc.identifier.urnURN:NBN:fi:jyu-202111305830
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/BookItem
dc.relation.isbn978-3-030-35745-0
dc.type.coarhttp://purl.org/coar/resource_type/c_3248
dc.description.reviewstatuspeerReviewed
dc.format.pagerange289-315
dc.relation.issn1613-5113
dc.type.versionacceptedVersion
dc.rights.copyright© Springer Nature Switzerland AG 2020
dc.rights.accesslevelopenAccessfi
dc.subject.ysotietoturva
dc.subject.ysokyberturvallisuus
dc.subject.ysotekoäly
dc.subject.ysoälytekniikka
dc.subject.ysoverkkohyökkäykset
dc.subject.ysopilvipalvelut
dc.subject.ysoälytalot
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p5479
jyx.subject.urihttp://www.yso.fi/onto/yso/p26189
jyx.subject.urihttp://www.yso.fi/onto/yso/p2616
jyx.subject.urihttp://www.yso.fi/onto/yso/p27260
jyx.subject.urihttp://www.yso.fi/onto/yso/p27466
jyx.subject.urihttp://www.yso.fi/onto/yso/p24167
jyx.subject.urihttp://www.yso.fi/onto/yso/p24344
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.relation.doi10.1007/978-3-030-35746-7_14
dc.type.okmA3


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