Please use this identifier to cite or link to this item: http://10.9.150.37:8080/dspace//handle/atmiyauni/1906
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dc.contributor.authorMR. AMIT M. GOHEL, DR. PRATIK A. VANJARA-
dc.date.accessioned2024-11-22T06:10:58Z-
dc.date.available2024-11-22T06:10:58Z-
dc.date.issued2022-
dc.identifier.urihttp://10.9.150.37:8080/dspace//handle/atmiyauni/1906-
dc.description.abstractIt is undeniably true that right now data is a really huge presence for all organizations or associations. In this way ensuring its security is vital and the security models driven by genuine datasets has become very significant. The activities dependent on military, government, business and regular citizens are connected to the security and accessibility of PC frameworks and organization. Starting here of safety, the organization security is a critical issue on the grounds that the limit of assaults is constantly ascending throughout the long term and they transform into be more modern and circulated. The target of this audit is to clarify and look at the most usually utilized datasets. This paper centers cyber security aspect to the various machine learning approaches such as Random Forest, SVM and KDDen_US
dc.language.isoenen_US
dc.subjectMACHINE LEARNINGen_US
dc.subjectBIG DATAen_US
dc.subjectINTERNET TRAFFICen_US
dc.subjectCYBER SECURITYen_US
dc.subjectDETECTION SYSTEMen_US
dc.titleA SURVEY: CYBER SECURITY FACET FOR MACHINE LEARNING ALGORITHMSen_US
dc.typeArticleen_US
Appears in Collections:01. Journal Articles

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