Please use this identifier to cite or link to this item:
https://hdl.handle.net/10316/107117
DC Field | Value | Language |
---|---|---|
dc.contributor.advisor | Shirazi, H. | - |
dc.contributor.advisor | Nowroozi, A. | - |
dc.contributor.author | Farzadnia, Ehsan | - |
dc.date.accessioned | 2023-06-08T03:45:00Z | - |
dc.date.available | 2023-06-08T03:45:00Z | - |
dc.date.issued | 2018-12-31 | - |
dc.identifier.uri | https://hdl.handle.net/10316/107117 | - |
dc.description | Documentos apresentados no âmbito do reconhecimento de graus e diplomas estrangeiros | por |
dc.description.abstract | Anomaly Detection is one of the significant and complex problems in computer networks security. Artifical Immune Systems are among the novel methods which have been mostly used by researchers in recent years. This System is a good prototype to develop Machine Learning techniques, and it can be a proper candidate for designing the next generation of intrusion detection systems owing to its many potentials. | pt |
dc.language.iso | other | pt |
dc.rights | openAccess | pt |
dc.subject | Network anomaly detection | pt |
dc.subject | Artificial immune system | pt |
dc.subject | Artificial life | pt |
dc.subject | Mature detector | pt |
dc.subject | Dendritic cell | pt |
dc.title | Provide a Novel Sophisticated Hybrid method for Intrusion Detection Using the Artificial Immune System (AIS) | pt |
dc.type | masterThesis | pt |
degois.publication.location | Malek Ashtar University of Technology | pt |
dc.date.embargo | 2018-12-31 | * |
uc.rechabilitacaoestrangeira | yes | pt |
uc.date.periodoEmbargo | 0 | pt |
item.fulltext | Com Texto completo | - |
item.languageiso639-1 | other | - |
item.openairecristype | http://purl.org/coar/resource_type/c_18cf | - |
item.openairetype | masterThesis | - |
item.grantfulltext | open | - |
item.cerifentitytype | Publications | - |
Appears in Collections: | UC - Reconhecimento de graus e diplomas estrangeiros |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Ehsan_Farzadnia_Official_Master-thesis_including_examiners_sheets.pdf | Dissertação | 19.51 MB | Adobe PDF | View/Open |
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