An adaptive trust model of web services

Su, Jindian; Guo, Hao; Yin, Gao

doi:10.1007/bf02828609

Cited by 11 publications

(5 citation statements)

References 5 publications

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“…This customized trust evaluation provides flexibility for service clients to have different trust values from the same feedback data. In [18], the trustworthiness of service provider in SOA is discussed. The service selection using the existing methods is practically complicated.…”

Section: Related Workmentioning

confidence: 99%

Quantitative Trust Management to Support QoS-Aware Service Selection in Service-Oriented Environments

Kim¹,

Doh²

2013

2013 International Conference on Parallel and Distributed Systems

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Owing to the black-box nature of services, selecting a trustworthy service that best fits users' requirements is greatly critical in service-oriented computing. Once a set of services fulfilling users' functional requirements are founded, one of these services invoked by the users depends mostly on the Quality of Services (QoS), particularly security, trust, and reputation. This paper proposes a trust management model to support service discovery and selection based on QoS. We define a quantitative trust evaluating method for dynamic service discovery and selection. The proposed model makes service consumers get trustworthy services possible. Our mechanism uses consumers' feedback to describe the trust degree of services and service providers. The service selection using the quantitative measurement rather than consumers' intuition allows selecting a highly reliable service accomplishing their quality requirements well. Finally, we give experimental results.

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Section: Related Workmentioning

confidence: 99%

Quantitative Trust Management to Support QoS-Aware Service Selection in Service-Oriented Environments

Kim¹,

Doh²

2013

2013 International Conference on Parallel and Distributed Systems

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“…However, few researchers have specifically studied the problem of reputation bootstrapping. The proposed framework [16] assigned the reputation of the provider to newly deployed services. The authors assessed provider reputation according to past experiences.…”

Section: Related Workmentioning

confidence: 99%

A Reputation Bootstrapping Model for E-Commerce Based on Fuzzy DEMATEL Method and Neural Network

2019

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Reputation evaluation plays an important role in determining the credibility of online entities. Especially in e-commerce systems, consumers usually give priority to this indicator when choosing vendors. Reputation bootstrapping, which can determine the default reputation value of new entities, is still a challenging problem. Most current bootstrapping methods fail to consider the complexity, the ambiguity of trust, or the reputation and internal correlation characteristics of influential factors in the prediction process. Therefore, in this paper, a novel reputation bootstrapping model that combines the fuzzy decision-making trial and evaluation laboratory (DEMATEL) method with neural network prediction is established. First, we adopt a fuzzy multi-criteria decision-making model, named fuzzy DEMATEL method to discuss the intrinsic causal relationships between influential factors and identify the critical success factors (CSFs) for reputation estimation. Then, we adopt back propagation (BP) neural network to generalize the correlations between the CSFs and the initial reputation value. Finally, a case study is constructed to verify the proposed model. The experimental results indicate that the proposed model has better accuracy and efficiency compared with other reputation bootstrapping methods.

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“…The framework proposed by Jin-Dian et al [65] assigns the provider reputation to its newly posted services. The authors suggest assessing the reputation of the provider based on its past experiences.…”

Section: Related Workmentioning

confidence: 99%

Estimating the reputation of newcomer web services using a regression-Based method

Tibermacine

Cherif

2018

Journal of Systems and Software

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In this paper, we propose a novel method to estimate the initial reputation values of newcomer web services. In fact, the reputation of web services is one of the criteria used for recommending services in service-oriented computing environments. The lack of evaluating the initial reputation values can subvert the performance of a service recommendation system making it vulnerable to different threats like whitewashing and Sybil attacks, which negatively affect its quality of recommendation. The proposed method uses Quality of Service (QoS) attributes from a side, and reputation values of similar services from the second side, to estimate the reputation values of newcomer services. Basically, it employs regression models, including Support Vector Regression, in the estimation process of the unknown reputation values of newcomers from their known QoS values. We demonstrate the efficiency of the method in estimating the reputation of newcomer services through statistical evidences gathered from experimentations conducted on a set of real-world web services.

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An adaptive trust model of web services

Cited by 11 publications

References 5 publications

Quantitative Trust Management to Support QoS-Aware Service Selection in Service-Oriented Environments

Quantitative Trust Management to Support QoS-Aware Service Selection in Service-Oriented Environments

A Reputation Bootstrapping Model for E-Commerce Based on Fuzzy DEMATEL Method and Neural Network

Estimating the reputation of newcomer web services using a regression-Based method

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