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A survey: Cyber security facet for machine learning algorithms

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dc.contributor.author Gohel, Amit M.
dc.contributor.author Vanjara, Pratik A.
dc.date.accessioned 2023-05-16T05:31:41Z
dc.date.available 2023-05-16T05:31:41Z
dc.date.issued 2022-01
dc.identifier.citation Gohel,A.&Vanjara,P.(2022).A survey: Cyber security facet for machine learning algorithms.International Multidisciplinary journal of applied research,1(6),11-19 en_US
dc.identifier.issn 2321-7073
dc.identifier.uri http://10.9.150.37:8080/dspace//handle/atmiyauni/965
dc.description.abstract It 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 KDD. en_US
dc.language.iso en en_US
dc.publisher International Multidisciplinary journal of applied research en_US
dc.subject MACHINE LEARNING en_US
dc.subject INTERNET TRAFFIC en_US
dc.subject BIG DATA en_US
dc.subject SECURITY en_US
dc.subject CYBER SECURITY en_US
dc.subject DETECTION SYSTEM en_US
dc.title A survey: Cyber security facet for machine learning algorithms en_US
dc.type Article en_US


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