Fuzzy trust evaluation based on consistency intensity for cloud services

Hu, Yi; Zhuang, Yi; Ni, Siru

doi:10.1108/k-03-2014-0058

Cited by 10 publications

(6 citation statements)

References 28 publications

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“…In our previous work [22], we proposed a fuzzy evaluation method based on group consistency intensity. Optimize the value of the semantic discount factor aim to maximize the consistency intensity between the individual evaluation value and the group evaluation value, thus the quantitative evaluation result can be obtained.…”

Section: Fuzzy Evaluation Methods Based On Minimum Deviationmentioning

confidence: 99%

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Maturity assessment model for aircraft collaborative design software solution

2018

Journal of Systems Engineering and Electronics

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In order to assure quality and control process in the development of the aircraft collaborative design software, a maturity assessment model is proposed. The requirements designinghouse of quality is designed to evaluate the maturity degree of the solution, and the evaluation results can help to manage and control the development process. Furthermore, a fuzzy evaluation method based on the minimum deviation is proposed to deal with the fuzzy information. The quantitative evaluation result of the maturity degree can be calculated by optimizing the semantic discount factor aim for the minimum deviation. Finally, this model is illustrated and analyzed by an example study of the aircraft collaborative design software.

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Section: Fuzzy Evaluation Methods Based On Minimum Deviationmentioning

confidence: 99%

“…A fuzzy evaluation method based on group consistency intensity is proposed in our previous work [21,22]. The interval values of evaluation can be synthesized by the DS theory and transformed to the certain value by the concept of the linguistic discount factor.…”

Section: Fuzzy Multi-attribute Decision Makingmentioning

confidence: 99%

Maturity assessment model for aircraft collaborative design software solution

2018

Journal of Systems Engineering and Electronics

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“…However, since the metrics are evaluated separately, it cannot be confirmed that the trust values would correctly represent the exact condition of the CSP compared to if these metrics are evaluated together. Similarly using fuzzy logic, [29] has evaluated trust from the following aspects: performance, reliability, security, price, and reputation. To develop an overall measure of trust value of the cloud providers, [30] uses Seguno fuzzy technique to process four criteria; scalability, availability, security, usability.…”

Section: Trust Evaluation Using Fuzzy Logicmentioning

confidence: 99%

Find my trustworthy fogs: A fuzzy-based trust evaluation framework

Rahman

Newaz

et al. 2020

Future Generation Computer Systems

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Find My Trustworthy Fogs: A Fuzzy-based Trust Evaluation Frameworkhttp://researchonline.ljmu.ac.uk/id/eprint/8724/ Article LJMU has developed LJMU Research Online for users to access the research output of the University more effectively. AbstractThe growth of IoT is proven with the massive amount of data generated in 2015, and expected to be even more in the years to come. Relying on the cloud to meet the expanding volume, variety, and velocity of data that the IoT generates may not be feasible. In the last two years, fog computing has become a considerably important research topic in an attempt to reduce the burden on cloud and solve cloud's inability to meet the IoT latency requirement. However, fog environment is different than in cloud since fog environment is far more distributed. Due to the dynamic nature of fog, backups such as redundant power supply would deem unnecessary, and relying on just one Internet Service Provider for their fog device would be sufficient. If obstacles arise in this fog environment, factors such as latency, availability or reliability would in turn be unstable. Fogs become harder to trust, and this issue is more complicated and challenging in comparison to the conventional cloud. This implies that trustworthiness in fog is an imperative issue that needs to be addressed. With the help of a broker, managing trust in a distributive environment can be tackled. Acting as an intermediary, a broker helps in facilitating negotiation between two parties. Although the brokering concept has been around for a long time and is widely used in the cloud, it is a new concept in fog computing. As of late, there are several research studies that incorporates broker in fog where these brokers focus towards pricing management. However to the best of our knowledge there is no literature on broker-based trust evaluation in fog service allocation. This is the first work that proposes broker-based trust evaluation framework that focuses on identifying a trustworthy fog to fulfill the user requests. In this paper, fuzzy logic is used as the basis for the evaluation while considering the availability and cost of fog. We propose Request Matching algorithm to identify a user request, and Fuzzybased Filtering algorithm to match the request with one of the predefined sets created and managed by the broker. In this paper, we present a use case that illustrates how fuzzy logic works in determining the trustworthiness of a fog. Our findings suggest that the algorithms can successfully provide users a trustworthy fog that matches their requirement. .bn (Wida Susanty Suhaili), g.m.lee@ljmu.ac.uk (Gyu-Myoung Lee)

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“…Also, these approaches do not reflect dynamic trust assessment of resources along a period of time. A fuzzy trust evaluation approach for cloud services is suggested by Huo et al [22]. The approach takes into consideration a set of cloud service attributes to assess the reputation based trust value.…”

Section: Related Workmentioning

confidence: 99%

“…The approach facilitates selection of a service according to the user requirements for various attributes. However, the approaches [21,22,23] are dependent on subjectively allocated weights to the various factors.…”

Section: Related Workmentioning

confidence: 99%

Preferences based Customized Trust Model for Assessment of Cloud Services

Deshpande¹,

Ingle²

2018

IJECE

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In cloud environment, many functionally similar cloud services are available. But, the services differ in Quality of Service (QoS) levels, offered by them. There is a diversity in user requirements about the expected qualities of cloud services. Trust is a measure to understand whether a cloud service can adequately meet the user requirements. Consequently, trust assessment plays a significant role in selecting the suitable cloud service. This paper proposes preferences based customized trust model (PBCTM) for trust assessment of cloud services. PBCTM takes into account user requirements about the expected quality of services in the form of preferences. Accordingly, it performs customized trust assessment based on the evidences of various attributes of cloud service. PBCTM enables elastic trust computation, which is responsive to dynamically changing user preferences with time. The model facilitates dynamic trust based periodic selection of cloud services according to varying user preferences. Experimental results demonstrate that the proposed preferences based customized trust model outperforms the other model in respect of accuracy and degree of satisfaction.Copyright c 2018 Institute of Advanced Engineering and Science.All rights reserved.Corresponding Author: Shilpa Deshpande, Department of Computer Engineering, College of Engineering Pune, Savitribai Phule Pune University, Pune, Maharashtra, India Email: shilpshree@yahoo.com INTRODUCTIONCloud computing has entered mainstream and received wider acceptance. It is increasingly adopted by individuals, small and medium scale enterprises (SMEs) and government organizations to run their critical applications. The reason for this acceptance is the characteristics of cloud like scalability, on demand service, anytime-anywhere access, economic benefits of pay-per-use, delegation of maintenance and administration, performance and disaster recovery. Cloud services have proliferated to include software as a service, database as a service, platform as a service, infrastructure as a service, security as a service and storage as a service [1]. Cloud environment still remains challenging to rely on because of factors like loss of control over applications and data, increased threats of security [2], performance issues related to virtualization [3], enterprise grade availability requirements [4,5,6] and adequately meeting Quality of Service (QoS) expectations of users [7].Cloud computing has compelling advantages yet challenges too. For an enterprise to adopt cloud, it is important that enterprise has a certain belief that advantages of cloud can be realized. Trust is a measure of this belief [8]. Conventionally, people rely on reputation [4,8], service level agreement (SLA) [6,9], self-assessment [8,9] and cloud auditing [8,9] for trust assessment in cloud environment. However, trust assessment in cloud environment poses further important issues, which are revealed as part of the following discussion.Reputation based traditional trust assessment technique relies on ...

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Fuzzy trust evaluation based on consistency intensity for cloud services

Cited by 10 publications

References 28 publications

Maturity assessment model for aircraft collaborative design software solution

Maturity assessment model for aircraft collaborative design software solution

Find my trustworthy fogs: A fuzzy-based trust evaluation framework

Preferences based Customized Trust Model for Assessment of Cloud Services

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