Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion.
<p>Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion.</p>
محفوظ في:
| المؤلف الرئيسي: | |
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| منشور في: |
2025
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| الموضوعات: | |
| الوسوم: |
إضافة وسم
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| _version_ | 1852022766323105792 |
|---|---|
| author | Abdullah Asım Yılmaz (20715311) |
| author_facet | Abdullah Asım Yılmaz (20715311) |
| author_role | author |
| dc.creator.none.fl_str_mv | Abdullah Asım Yılmaz (20715311) |
| dc.date.none.fl_str_mv | 2025-02-12T18:41:00Z |
| dc.identifier.none.fl_str_mv | 10.1371/journal.pone.0316253.g013 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/figure/Confusion_matrices_obtained_by_applying_the_proposed_method_to_the_NSL-KDD_dataset_for_five_types_of_intrusion_/28403711 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified many new types kddcup &# 8217 empirical findings show attackers every day 44 %, 90 proposed model successfully particle swarm optimisation outperforms alternative schemes accuracy values obtained deep neural network trained network models based hybrid architecture novel deep learning novel deep based architecture hybrid system art schemes alternative state based framework architecture design computer network various strategies trained dnn three well suggested method still elusive significant role robust system recent years optimised way nb15 datasets main contribution information security important challenge hyperparameter optimisation data gathering critical element |
| dc.title.none.fl_str_mv | Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion. |
| dc.type.none.fl_str_mv | Image Figure info:eu-repo/semantics/publishedVersion image |
| description | <p>Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion.</p> |
| eu_rights_str_mv | openAccess |
| id | Manara_e304c00efde3a9dce3dfdaa8a04f4496 |
| identifier_str_mv | 10.1371/journal.pone.0316253.g013 |
| network_acronym_str | Manara |
| network_name_str | ManaraRepo |
| oai_identifier_str | oai:figshare.com:article/28403711 |
| publishDate | 2025 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion.Abdullah Asım Yılmaz (20715311)Biological Sciences not elsewhere classifiedMathematical Sciences not elsewhere classifiedInformation Systems not elsewhere classifiedmany new typeskddcup &# 8217empirical findings showattackers every day44 %, 90proposed model successfullyparticle swarm optimisationoutperforms alternative schemesaccuracy values obtaineddeep neural networktrained network modelsbased hybrid architecturenovel deep learningnovel deepbased architecturehybrid systemart schemesalternative statebased frameworkarchitecture designcomputer networkvarious strategiestrained dnnthree wellsuggested methodstill elusivesignificant rolerobust systemrecent yearsoptimised waynb15 datasetsmain contributioninformation securityimportant challengehyperparameter optimisationdata gatheringcritical element<p>Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion.</p>2025-02-12T18:41:00ZImageFigureinfo:eu-repo/semantics/publishedVersionimage10.1371/journal.pone.0316253.g013https://figshare.com/articles/figure/Confusion_matrices_obtained_by_applying_the_proposed_method_to_the_NSL-KDD_dataset_for_five_types_of_intrusion_/28403711CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/284037112025-02-12T18:41:00Z |
| spellingShingle | Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion. Abdullah Asım Yılmaz (20715311) Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified many new types kddcup &# 8217 empirical findings show attackers every day 44 %, 90 proposed model successfully particle swarm optimisation outperforms alternative schemes accuracy values obtained deep neural network trained network models based hybrid architecture novel deep learning novel deep based architecture hybrid system art schemes alternative state based framework architecture design computer network various strategies trained dnn three well suggested method still elusive significant role robust system recent years optimised way nb15 datasets main contribution information security important challenge hyperparameter optimisation data gathering critical element |
| status_str | publishedVersion |
| title | Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion. |
| title_full | Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion. |
| title_fullStr | Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion. |
| title_full_unstemmed | Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion. |
| title_short | Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion. |
| title_sort | Confusion matrices obtained by applying the proposed method to the NSL-KDD dataset, for five types of intrusion. |
| topic | Biological Sciences not elsewhere classified Mathematical Sciences not elsewhere classified Information Systems not elsewhere classified many new types kddcup &# 8217 empirical findings show attackers every day 44 %, 90 proposed model successfully particle swarm optimisation outperforms alternative schemes accuracy values obtained deep neural network trained network models based hybrid architecture novel deep learning novel deep based architecture hybrid system art schemes alternative state based framework architecture design computer network various strategies trained dnn three well suggested method still elusive significant role robust system recent years optimised way nb15 datasets main contribution information security important challenge hyperparameter optimisation data gathering critical element |