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dc.contributor.authorBodström, Tero
dc.contributor.authorHämäläinen, Timo
dc.contributor.editorChen, Xuemin
dc.contributor.editorSen, Arunabha
dc.contributor.editorLi, Wei Wayne
dc.contributor.editorThai, My T.
dc.date.accessioned2018-12-19T08:24:35Z
dc.date.available2019-11-18T22:35:39Z
dc.date.issued2018
dc.identifier.citationBodström, T., & Hämäläinen, T. (2018). A Novel Method for Detecting APT Attacks by Using OODA Loop and Black Swan Theory. In X. Chen, A. Sen, W. W. Li, & M. T. Thai (Eds.), <i>Computational Data and Social Networks : 7th International Conference, CSoNet 2018, December 18-20, 2018, Shanghai, China, Proceedings</i> (pp. 498-509). Springer. Lecture Notes in Computer Science, 11280. <a href="https://doi.org/10.1007/978-3-030-04648-4_42" target="_blank">https://doi.org/10.1007/978-3-030-04648-4_42</a>
dc.identifier.otherCONVID_28767782
dc.identifier.otherTUTKAID_79786
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/60675
dc.description.abstractAdvanced Persistent Threat(APT) attacks are a major concern for the modern societal digital infrastructures due to their highly sophisticated nature. The purpose of these attacks varies from long period espionage in high level environment to causing maximal destruction for targeted cyber environment. Attackers are skilful and well funded by governments in many cases. Due to sophisticated methods it is highly important to study proper countermeasures to detect these attacks as early as possible. Current detection methods under-performs causing situations where an attack can continue months or even years in a targeted environment. We propose a novel method for analysing APT attacks through OODA loop and Black Swan theory by defining them as a multivector multi-stage attacks with continuous strategical ongoing campaign. Additionally it is important to notice that for developing better performing detection methods, we have to find the most common factor within these attacks. We can state that the most common factor of APT attacks is communication, thus environment has to be developed in a way that we are able to capture complete network flow and analyse it.fi
dc.format.extent544
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofComputational Data and Social Networks : 7th International Conference, CSoNet 2018, December 18-20, 2018, Shanghai, China, Proceedings
dc.relation.ispartofseriesLecture Notes in Computer Science
dc.rightsIn Copyright
dc.subject.otherAdvanced Persistent Thread (APT)
dc.subject.otherOODA loop
dc.subject.otherBlack Swan theory
dc.subject.othernetwork anomaly detection
dc.titleA Novel Method for Detecting APT Attacks by Using OODA Loop and Black Swan Theory
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201812145146
dc.contributor.laitosInformaatioteknologian tiedekuntafi
dc.contributor.laitosFaculty of Information Technologyen
dc.contributor.oppiaineTietojärjestelmätiedefi
dc.contributor.oppiaineInformation Systems Scienceen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2018-12-14T13:15:20Z
dc.relation.isbn978-3-030-04647-7
dc.type.coarhttp://purl.org/coar/resource_type/c_5794
dc.description.reviewstatuspeerReviewed
dc.format.pagerange498-509
dc.relation.issn0302-9743
dc.relation.numberinseries11280
dc.type.versionacceptedVersion
dc.rights.copyright© Springer Nature Switzerland AG 2018.
dc.rights.accesslevelopenAccessfi
dc.relation.conferenceInternational Conference on Computational Social Networks
dc.format.contentfulltext
dc.rights.urlhttp://rightsstatements.org/page/InC/1.0/?language=en
dc.rights.accessrights
dc.relation.doi10.1007/978-3-030-04648-4_42
dc.type.okmA4


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