Please use this identifier to cite or link to this item: http://10.9.150.37:8080/dspace//handle/atmiyauni/965
Title: A survey: Cyber security facet for machine learning algorithms
Authors: Gohel, Amit M.
Vanjara, Pratik A.
Keywords: MACHINE LEARNING
INTERNET TRAFFIC
BIG DATA
SECURITY
CYBER SECURITY
DETECTION SYSTEM
Issue Date: Jan-2022
Publisher: International Multidisciplinary journal of applied research
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
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.
URI: http://10.9.150.37:8080/dspace//handle/atmiyauni/965
ISSN: 2321-7073
Appears in Collections:01. VSC CSIT FP Journal Articles

Files in This Item:
File Description SizeFormat 
336) 22079_Pratik Anilkumar Vanjara.pdf1.03 MBAdobe PDFView/Open
Show full item record


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.