A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments
Saved in:
| Main Author: | |
|---|---|
| Format: | masterThesis |
| Published: |
2020
|
| Subjects: | |
| Online Access: | https://eprints.kfupm.edu.sa/id/eprint/143636/1/Razan_Al-Fageer_g202203760_thesis.pdf |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1864513387539464193 |
|---|---|
| author | unknown |
| author_facet | unknown |
| author_role | author |
| dc.creator.*.fl_str_mv | unknown |
| dc.date.*.fl_str_mv | 2020 |
| dc.format.none.fl_str_mv | application/pdf |
| dc.identifier.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/143636/1/Razan_Al-Fageer_g202203760_thesis.pdf A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments. Masters thesis, King Fahd University of Petroleum and Minerals. |
| dc.language.none.fl_str_mv | en |
| dc.relation.none.fl_str_mv | https://eprints.kfupm.edu.sa/id/eprint/143636/ |
| dc.rights.*.fl_str_mv | info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Computer Systems |
| dc.title.none.fl_str_mv | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments |
| dc.type.none.fl_str_mv | Thesis NonPeerReviewed info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/masterThesis |
| eu_rights_str_mv | openAccess |
| format | masterThesis |
| id | KFUPM_c5b438d5392275c2b527672b6f9cec1d |
| identifier_str_mv | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments. Masters thesis, King Fahd University of Petroleum and Minerals. |
| language_invalid_str_mv | en |
| network_acronym_str | KFUPM |
| network_name_str | King Fahd University of Petroleum and Minerals |
| oai_identifier_str | oai::143636 |
| publishDate | 2020 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| spelling | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT EnvironmentsComputerSystemsThesisNonPeerReviewedinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttps://eprints.kfupm.edu.sa/id/eprint/143636/1/Razan_Al-Fageer_g202203760_thesis.pdf A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments. Masters thesis, King Fahd University of Petroleum and Minerals. enhttps://eprints.kfupm.edu.sa/id/eprint/143636/2020info:eu-repo/semantics/openAccessunknownoai::1436362025-08-10T06:03:03Z |
| spellingShingle | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments unknown Computer Systems |
| status_str | publishedVersion |
| title | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments |
| title_full | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments |
| title_fullStr | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments |
| title_full_unstemmed | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments |
| title_short | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments |
| title_sort | A Hybrid Machine Learning System for Detection of Known and Zero-day Attacks in IoMT Environments |
| topic | Computer Systems |
| url | https://eprints.kfupm.edu.sa/id/eprint/143636/1/Razan_Al-Fageer_g202203760_thesis.pdf |