A multi-dimensional trust evaluation model for large-scale P2P computing

Li, Xiaoyong; Zhou, Feng; Yang, Xudong

doi:10.1016/j.jpdc.2011.01.007

Cited by 73 publications

(45 citation statements)

References 22 publications

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“…To increase the flexibility of network computing systems, many researchers have proposed trust-based approaches, i.e., the trust information sharing mechanisms, algorithms for selecting entities to trust, evaluation mechanisms and so on in distributed systems, such as peer-topeer networks [2,3,17] , ad hoc sensor network [18] , ubiquitous computing, and electronic commerce communities. However, due to the uncertainty of the trust cognition and the inherent human subjective nature in the trust evaluation, there are still big challenges needed to be addressed.…”

Section: Trust and Reputation Modelsmentioning

confidence: 99%

“…There are extended and multidimensional trust factors that have influences on the trust evaluation. Li et al [3] proposed a trust model for large-scale P2P computing, in which multiple factors are incorporated to reflect the complexity of trust, and the weights are dynamically assigned to the factors by weighted moving average and ordered weighted averaging (WMA-OWA) combination algorithms. Wang and Wu [19] proposed a multidimensional evidence-based trust management system with multi-paths to conduct trust computation on any arbitrarily complex trusted graph.…”

Section: Trust and Reputation Modelsmentioning

confidence: 99%

“…To ensure the normal operation and running of the whole cloud service system, trust management is essential for individuals to evaluate others and make satisfactory selection and thus can interact with the ones with high reputation [2,3] . Therefore, there should be a mechanism which helps users to make right decisions on selecting trustworthy cloud services for further interactions.…”

Section: Introductionmentioning

confidence: 99%

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A multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning approach

Fan

Yang

Perros

et al. 2014

Int. J. Autom. Comput.

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Abstract:In the last few years, cloud computing as a new computing paradigm has gone through significant development, but it is also facing many problems. One of them is the cloud service selection problem. As increasingly boosting cloud services are offered through the internet and some of them may be not reliable or even malicious, how to select trustworthy cloud services for cloud users is a big challenge. In this paper, we propose a multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning (ER) approach that integrates both perception-based trust value and reputation based trust value, which are derived from direct and indirect trust evidence respectively, to identify trustworthy services. Here, multi-dimensional trust evidence, which reflects the trustworthiness of cloud services from different aspects, is elicited in the form of historical users feedback ratings. Then, the ER approach is applied to aggregate the multi-dimensional trust ratings to obtain the real-time trust value and select the most trustworthy cloud service of certain type for the active users. Finally, the fresh feedback from the active users will update the trust evidence for other service users in the future.

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Section: Trust and Reputation Modelsmentioning

confidence: 99%

Section: Trust and Reputation Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

A multi-dimensional trust-aware cloud service selection mechanism based on evidential reasoning approach

Fan

Yang

Perros

et al. 2014

Int. J. Autom. Comput.

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“…A large number of trust solutions appeared in various distributed networks, such as P2P, Ad hoc, WSN [2] [4][5][6][7].…”

Section: Some Elements Of Trust Managementmentioning

confidence: 99%

Distributed Trust Management Mechanism for the Internet of Things

Wang¹,

Sun²,

Yu³

et al. 2013

Proceedings of the 2nd International Conference on Computer Science and Electronics Engineering (ICCSEE 2013)

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Abstract-Trust management provides a potential solution for the security issues of distributed networks. However, there are rare researches about the trust mechanism for IoT in the literature. A new distributed trust management mechanism for IoT is established in this paper. Firstly, we extract three basic elements-service, decision-making and self-organizing, of trust management from the investigated trust solutions. Then, based on a service model, we establish a trust management framework for the layered IoT, which is decomposed into three layers: sensor layer, core layer and application layer. Finally, we use fuzzy set theory and formal semantics-based language to perform the layered trust mechanism. The proposed trust conception, layered service model and formal method provide a general framework for the study of trust management for the IoT, and further provide a significant reference for the development of sound trust models for IoT.

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“…Last several years, with the rapid development of computer network, distributed computing system has a very vast application prospect and potential utility value, which integrates a large number of relative technology together [3][4], which opens up a wealth of opportunities for different applications, such as information processing, energy management, data delivery and so on [5][6][7] . More attention has been paid to the further development and more applications emerging, distributed computing is no longer confined to the traditional area, for example cloud computing and big data, moreover improves the efficiency of computing tasks while reducing energy consumption, and additionally augment the safety and security systems [8]. Large scale distributed computing infrastructure are unified computing platform which tries to connect and share all resources in the Internet, including computation resource, storage resource, information resource, knowledge resource and equipment for scientific research, and then solves the problems of large-scale engineering computing and commercial computing as well.…”

Section: Introductionmentioning

confidence: 99%