dc.contributor.author | Ahmed, Nada | |
dc.contributor.author | Ojha, Varun Kumar | |
dc.contributor.author | Abraham, Ajith | |
dc.date.accessioned | 2016-05-11T12:44:37Z | |
dc.date.available | 2016-05-11T12:44:37Z | |
dc.date.issued | 2015 | |
dc.identifier.citation | Journal of Information Assurance and Security. 2015, vol. 10, issue 5, p. 226-231. | cs |
dc.identifier.issn | 1554-1010 | |
dc.identifier.issn | 1554-1029 | |
dc.identifier.uri | http://hdl.handle.net/10084/111547 | |
dc.description.abstract | Cloud 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.language.iso | en | cs |
dc.publisher | Dynamic Publishers | cs |
dc.relation.ispartofseries | Journal of Information Assurance and Security | cs |
dc.subject | cloud computing | cs |
dc.subject | risk assessment | cs |
dc.subject | adaptive neuro-fuzzy inference system | cs |
dc.subject | feature selection | cs |
dc.subject | ensemble | cs |
dc.subject | genetic algorithm | cs |
dc.title | An ensemble of neuro-fuzzy model for assessing risk in cloud computing environment | cs |
dc.type | article | cs |
dc.type.status | Peer-reviewed | cs |
dc.description.source | Web of Science | cs |
dc.description.volume | 10 | cs |
dc.description.issue | 5 | cs |
dc.description.lastpage | 231 | cs |
dc.description.firstpage | 226 | cs |
dc.identifier.wos | 000373692800003 | |