| fullrecord |
[{"key": "dc.contributor.advisor", "value": "H\u00e4m\u00e4l\u00e4inen, Timo", "language": "", "element": "contributor", "qualifier": "advisor", "schema": "dc"}, {"key": "dc.contributor.author", "value": "Arikainen, Anna", "language": "", "element": "contributor", "qualifier": "author", "schema": "dc"}, {"key": "dc.date.accessioned", "value": "2023-05-22T10:21:10Z", "language": null, "element": "date", "qualifier": "accessioned", "schema": "dc"}, {"key": "dc.date.available", "value": "2023-05-22T10:21:10Z", "language": null, "element": "date", "qualifier": "available", "schema": "dc"}, {"key": "dc.date.issued", "value": "2023", "language": "", "element": "date", "qualifier": "issued", "schema": "dc"}, {"key": "dc.identifier.uri", "value": "https://jyx.jyu.fi/handle/123456789/87053", "language": null, "element": "identifier", "qualifier": "uri", "schema": "dc"}, {"key": "dc.description.abstract", "value": "T\u00e4m\u00e4 pro gradu -tutkielma k\u00e4sittelee Darknet 2020 -nimisen datasetin testaamista random forest-, gradient boosting- ja logistic regression-algoritmeilla. Tutkimus toteutettiin konstruktiivisena tutkimuksena. Tutkimuksen aineisto koostuu New Brunswick yliopiston tutkijoiden Habibi Lashkarin, Kaurin ja Rahalin tekem\u00e4st\u00e4 artikkelista DIDarknet: A Contemporary Approach to Detect and Characterize the Darknet Traffic using Deep Image Learning sek\u00e4 heid\u00e4n tuottamastaan Darknet 2020 -datasetist\u00e4. Tutkimuksen tarkoituksena oli selvitt\u00e4\u00e4, miten koneoppimisen algoritmit selviytyv\u00e4t datasetiss\u00e4 olevan darknet-tietoliikennett\u00e4 imitoivan datan luokitellusta sek\u00e4 verrata saatuja tuloksia tutkijoiden esittelem\u00e4\u00e4n syv\u00e4oppimisen malliin nimelt\u00e4 DIDarknet.\n\nTutkimuksen lopputuloksena voidaan n\u00e4hd\u00e4 useamman eri koneoppimisalgoritmin tarkkudet luokitella datasetin tietoliikenne Label-ominaisuuden perusteella. Random forest -algoritmi suoriutui luokitteluteht\u00e4v\u00e4st\u00e4 huomattavasti kahta muuta algoritmia paremmin. Tutkimuksen perusteella voidaan n\u00e4hd\u00e4, ett\u00e4 DIDarknet on suoriutunut darknet-liikenteen luokittelusta ylivoimaisesti paremmin kuin tutkielmassa esiintyv\u00e4t ML-algoritmit.", "language": "fi", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.abstract", "value": "This master's thesis deals with testing the Darknet 2020 dataset with random forest, gradient boosting and logistic regression algorithms. The study was carried out as a constructive study. The material of the study consists of the article \\emph{DIDarknet: A Contemporary Approach to Detect and Characterize the Darknet Traffic using Deep Image Learning} by researchers Habibi Lashkari, Kaur and Rahali of the University of New Brunswick and the Darknet 2020 dataset produced by them. The purpose of the study was to find out how the machine learning algorithms cope with the classification of the data simulating darknet communication in the dataset, and to compare the obtained results with the deep learning model presented by the researchers called DIDarknet.\n\nThe final result of the research is the accuracy of several different machine learning algorithms to classify data traffic based on the Label feature. The random forest algorithm performed the classification task significantly better than the other two algorithms. On the basis of the research, it can be concluded that DIDarknet has performed by far better than the ML algorithms appearing in the thesis in the classification of darknet traffic.", "language": "en", "element": "description", "qualifier": "abstract", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Submitted by Paivi Vuorio (paelvuor@jyu.fi) on 2023-05-22T10:21:10Z\nNo. of bitstreams: 0", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.description.provenance", "value": "Made available in DSpace on 2023-05-22T10:21:10Z (GMT). No. of bitstreams: 0\n Previous issue date: 2023", "language": "en", "element": "description", "qualifier": "provenance", "schema": "dc"}, {"key": "dc.format.extent", "value": "66", "language": "", "element": "format", "qualifier": "extent", "schema": "dc"}, {"key": "dc.language.iso", "value": "fin", "language": null, "element": "language", "qualifier": "iso", "schema": "dc"}, {"key": "dc.rights", "value": "In Copyright", "language": null, "element": "rights", "qualifier": null, "schema": "dc"}, {"key": "dc.subject.other", "value": "darknet", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "random forest", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "gradient boosting", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "logistic regression", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.subject.other", "value": "konvoluutioneuroverkko", "language": "", "element": "subject", "qualifier": "other", "schema": "dc"}, {"key": "dc.title", "value": "Darknet-liikenteen analysointi koneoppimisalgoritmeilla", "language": "", "element": "title", "qualifier": null, "schema": "dc"}, {"key": "dc.type", "value": "master thesis", "language": null, "element": "type", "qualifier": null, "schema": "dc"}, {"key": "dc.identifier.urn", "value": "URN:NBN:fi:jyu-202305223126", "language": "", "element": "identifier", "qualifier": "urn", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Master\u2019s thesis", "language": "en", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.type.ontasot", "value": "Pro gradu -tutkielma", "language": "fi", "element": "type", "qualifier": "ontasot", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Informaatioteknologian tiedekunta", "language": "fi", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.faculty", "value": "Faculty of Information Technology", "language": "en", "element": "contributor", "qualifier": "faculty", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Informaatioteknologia", "language": "fi", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.department", "value": "Information Technology", "language": "en", "element": "contributor", "qualifier": "department", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "Jyv\u00e4skyl\u00e4n yliopisto", "language": "fi", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.contributor.organization", "value": "University of Jyv\u00e4skyl\u00e4", "language": "en", "element": "contributor", "qualifier": "organization", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Tietotekniikka", "language": "fi", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "dc.subject.discipline", "value": "Mathematical Information Technology", "language": "en", "element": "subject", "qualifier": "discipline", "schema": "dc"}, {"key": "yvv.contractresearch.funding", "value": "0", "language": "", "element": "contractresearch", "qualifier": "funding", "schema": "yvv"}, {"key": "dc.type.coar", "value": "http://purl.org/coar/resource_type/c_bdcc", "language": null, "element": "type", "qualifier": "coar", "schema": "dc"}, {"key": "dc.rights.copyright", "value": "\u00a9 The Author(s)", "language": null, "element": "rights", "qualifier": "copyright", "schema": "dc"}, {"key": "dc.rights.accesslevel", "value": "openAccess", "language": null, "element": "rights", "qualifier": "accesslevel", "schema": "dc"}, {"key": "dc.type.publication", "value": "masterThesis", "language": null, "element": "type", "qualifier": "publication", "schema": "dc"}, {"key": "dc.subject.oppiainekoodi", "value": "602", "language": "", "element": "subject", "qualifier": "oppiainekoodi", "schema": "dc"}, {"key": "dc.subject.yso", "value": "anonyymiverkot", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "algoritmit", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "koneoppiminen", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "neuroverkot", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.subject.yso", "value": "syv\u00e4oppiminen", "language": null, "element": "subject", "qualifier": "yso", "schema": "dc"}, {"key": "dc.rights.url", "value": "https://rightsstatements.org/page/InC/1.0/", "language": null, "element": "rights", "qualifier": "url", "schema": "dc"}]
|