An ensemble of neuro-fuzzy model for assessing risk in cloud computing environment

dc.contributor.authorAhmed, Nada
dc.contributor.authorOjha, Varun Kumar
dc.contributor.authorAbraham, Ajith
dc.date.accessioned2016-05-11T12:44:37Z
dc.date.available2016-05-11T12:44:37Z
dc.date.issued2015
dc.description.abstractCloud computing is one of the hottest technologies in IT field. It provides computational resources as general utilities that can be leased and released by users in an on-demand fashion. Companies around the globe showing high interest in adopting cloud computing technology, however, cloud computing adaptation comes with greater risks that need to be assessed. In this research, an ensemble of adaptive neuro-fuzzy inference system (ANFIS) is proposed to assess risk factors in cloud computing environment. In the proposed framework, various membership functions were used to construct ANFIS model and finally, an ensemble of ANFIS models was constructed using an evolutionary algorithm. Empirical results indicate a high performance of our proposed models in assessing risk in cloud environment.cs
dc.description.firstpage226cs
dc.description.issue5cs
dc.description.lastpage231cs
dc.description.sourceWeb of Sciencecs
dc.description.volume10cs
dc.identifier.citationJournal of Information Assurance and Security. 2015, vol. 10, issue 5, p. 226-231.cs
dc.identifier.issn1554-1010
dc.identifier.issn1554-1029
dc.identifier.urihttp://hdl.handle.net/10084/111547
dc.identifier.wos000373692800003
dc.language.isoencs
dc.publisherDynamic Publisherscs
dc.relation.ispartofseriesJournal of Information Assurance and Securitycs
dc.subjectcloud computingcs
dc.subjectrisk assessmentcs
dc.subjectadaptive neuro-fuzzy inference systemcs
dc.subjectfeature selectioncs
dc.subjectensemblecs
dc.subjectgenetic algorithmcs
dc.titleAn ensemble of neuro-fuzzy model for assessing risk in cloud computing environmentcs
dc.typearticlecs
dc.type.statusPeer-reviewedcs

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