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A fuzzy logic based risk assessment approach for evaluating and prioritizing risks in cloud computing environment

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dc.citedby8
dc.contributor.authorAmini A.en_US
dc.contributor.authorJamil N.en_US
dc.contributor.authorAhmad A.R.en_US
dc.contributor.authorSulaiman H.en_US
dc.contributor.authorid57202440982en_US
dc.contributor.authorid36682671900en_US
dc.contributor.authorid35589598800en_US
dc.contributor.authorid54903312800en_US
dc.date.accessioned2023-05-29T06:56:50Z
dc.date.available2023-05-29T06:56:50Z
dc.date.issued2018
dc.descriptionCloud computing; Computer circuits; Fuzzy logic; Numerical methods; Risk management; Risk perception; Security of data; Assessment approaches; Business environments; Cloud computing environments; Conceptual model; Management efforts; Numerical values; On-demand services; Quantitative data; Risk assessmenten_US
dc.description.abstractCloud computing is an innovative and popular paradigm in information technology. It delivers on-demand services by offering numerous advantages such as reduced management effort and efficient resource usage which would lead to economic saving. However, the associated flexibility and elasticity have caused many information security issues in a business environment. In such scenarios, all risk factors must be managed based on their probable effects on assets. Moreover, risk assessment as a core of risk management, estimates and prioritizes risks to reduce their impact and maximize the benefits of cloud computing for system providers and clients. In this paper, we adopt fuzzy logic to deal with insufficient information and estimate the severity and the likelihood of each risk mathematically. The aim of this paper is to develop a conceptual model to prioritize risks based on severity and probability. For estimating risk, human knowledge and expertise need to be integrated into role based circumstance. As a result, fuzzy logic is presented in this paper and the incenter on centroid method is proposed to convert linguistics data to numerical value in order to quantify the rate of risk. On the other hand, fuzzy logic has been used to deal with human experience as insufficient information to obtain the quantitative data due to the risk characterizing factors. � Springer International Publishing AG 2018.en_US
dc.description.natureFinalen_US
dc.identifier.doi10.1007/978-3-319-59427-9_67
dc.identifier.epage659
dc.identifier.scopus2-s2.0-85048360756
dc.identifier.spage650
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85048360756&doi=10.1007%2f978-3-319-59427-9_67&partnerID=40&md5=99d713eaf570e8ea9195277920eb94f5
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/24200
dc.identifier.volume5
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.sourceScopus
dc.sourcetitleLecture Notes on Data Engineering and Communications Technologies
dc.titleA fuzzy logic based risk assessment approach for evaluating and prioritizing risks in cloud computing environmenten_US
dc.typeBook Chapteren_US
dspace.entity.typePublication
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