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dc.contributor.authorSipola, Tuomo
dc.contributor.authorJuvonen, Antti
dc.contributor.authorLehtonen, Joel
dc.contributor.editorIliadis, Lazaros
dc.contributor.editorJayne, Chrisina
dc.date.accessioned2012-06-05T09:10:09Z
dc.date.available2012-06-05T09:10:09Z
dc.date.issued2011
dc.identifier.citationSipola, T., Juvonen, A., & Lehtonen, J. (2011). Anomaly detection from network logs using diffusion maps. In L. Iliadis, & C. Jayne (Eds.), <i>Engineering Applications of Neural Networks</i> (pp. 172-181). Springer. IFIP Advances in Information and Communication Technology, 363. <a href="https://doi.org/10.1007/978-3-642-23957-1_20" target="_blank">https://doi.org/10.1007/978-3-642-23957-1_20</a>
dc.identifier.otherCONVID_20672180
dc.identifier.otherTUTKAID_46410
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/37967
dc.description.abstractThe goal of this study is to detect anomalous queries from network logs using a dimensionality reduction framework. The fequencies of 2-grams in queries are extracted to a feature matrix. Dimensionality reduction is done by applying diffusion maps. The method is adaptive and thus does not need training before analysis. We tested the method with data that includes normal and intrusive traffic to a web server. This approach finds all intrusions in the dataset.
dc.language.isoeng
dc.publisherSpringer
dc.relation.ispartofEngineering Applications of Neural Networks
dc.relation.ispartofseriesIFIP Advances in Information and Communication Technology
dc.relation.urihttp://www.springerlink.com/index/N615170400W21N13.pdf
dc.rightsIn Copyright
dc.subject.otherhyökkäyksen havaitseminen
dc.subject.otherpoikkeavuuden havaitseminen
dc.subject.othern-grammit
dc.subject.otherdiffuusiokartta
dc.subject.otherintrusion detection
dc.subject.otheranomaly detection
dc.subject.othern-grams
dc.subject.otherdiffusion map
dc.titleAnomaly detection from network logs using diffusion maps
dc.typeconferenceObject
dc.identifier.urnURN:NBN:fi:jyu-201206051800
dc.contributor.laitosTietotekniikan laitosfi
dc.contributor.laitosDepartment of Mathematical Information Technologyen
dc.contributor.oppiaineTietotekniikkafi
dc.contributor.oppiaineMathematical Information Technologyen
dc.type.urihttp://purl.org/eprint/type/ConferencePaper
dc.date.updated2012-06-05T03:30:05Z
dc.relation.isbn978-3-642-23956-4
dc.type.coarhttp://purl.org/coar/resource_type/c_5794
dc.description.reviewstatuspeerReviewed
dc.format.pagerange172-181
dc.relation.issn1868-4238
dc.type.versionacceptedVersion
dc.rights.copyright© Springer. This is an electronic final draft version of an article whose final and definitive form has been published by Springer.
dc.rights.accesslevelopenAccess
dc.subject.ysotiedonlouhinta
dc.subject.ysokoneoppiminen
jyx.subject.urihttp://www.yso.fi/onto/yso/p5520
jyx.subject.urihttp://www.yso.fi/onto/yso/p21846
dc.rights.urlhttps://rightsstatements.org/page/InC/1.0/
dc.relation.doi10.1007/978-3-642-23957-1_20
dc.type.okmA4


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