Evaluation Approach of Subjective Trust Based on Cloud Model

Wang, Shouxin; Zhang, Li; Li, Hesong

doi:10.3724/sp.j.1001.2010.03501

Cited by 36 publications

(7 citation statements)

References 10 publications

(11 reference statements)

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“…Some researchers put forward evolutionary algorithms combined trust mechanisms [30], [31]. Wang et al [32] proposed the trust assessment method based on the cloud model. Xie et al [33] designed the double excitation and deception detection based trust model.…”

Section: B Trust Management Strategiesmentioning

confidence: 99%

A Trust-Based Agent Learning Model for Service Composition in Mobile Cloud Computing Environments

Cao

et al. 2019

IEEE Access

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Mobile cloud computing has the features of resource constraints, openness, and uncertainty which leads to the high uncertainty on its quality of service (QoS) provision and serious security risks. Therefore, when faced with complex service requirements, an efficient and reliable service composition approach is extremely important. In addition, preference learning is also a key factor to improve user experiences. In order to address them, this paper introduces a three-layered trust-enabled service composition model for the mobile cloud computing systems. Based on the fuzzy comprehensive evaluation method, we design a novel and integrated trust management model. Service brokers are equipped with a learning module enabling them to better analyze customers' service preferences, especially in cases when the details of a service request are not totally disclosed. Because traditional methods cannot totally reflect the autonomous collaboration between the mobile cloud entities, a prototype system based on the multi-agent platform JADE is implemented to evaluate the efficiency of the proposed strategies. The experimental results show that our approach improves the transaction success rate and user satisfaction. INDEX TERMS Mobile cloud computing, service composition, trust management, user preference learning, multi-agent technology.

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Section: B Trust Management Strategiesmentioning

confidence: 99%

A Trust-Based Agent Learning Model for Service Composition in Mobile Cloud Computing Environments

Cao

et al. 2019

IEEE Access

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“…The fuzzy AHP theory is used which is based on entropy weight mechanism. Wagng et al [34] have suggested that the existing approaches which are based on probability and fuzzy set theory didn't give enough importance to uncertainty. To eliminate this problem, the authors have proposed a quantifiable subjective trust evaluation approach.…”

Section: Fuzzy Logic Based Trust Model In Cloudmentioning

confidence: 99%

Trust Models in Cloud Computing: A Review

Ritu¹,

Randhawa²,

Jain³

2017

IJWMT

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It is common to hear that big or small organizations are moving to cloud computing for its scalability and cost savings. But, how do you decide which cloud provider to trust? Trust is a vital factor, especially for service oriented systems in the area of Information Technology and Security. Several issues have been raised by enterprises and individuals concerning the reliability of the cloud resources. In cloud computing, trust helps the consumer to choose the service of a cloud service provider for storing and processing their sensitive information. In this paper, a methodical literature analysis of trust management and existing trust models is presented to evaluate trust based on various QoS parameters. Key research issues and future research directions in existing literature are also suggested.

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“…Wang et al [40] proposed a subjective trust quantification evaluation method based on a cloud model. The method introduced three digital characteristics of subjective trust to quantify on object's trust and the changes of object trust were described by a mutative trust cloud.…”

Section: Trust Modelmentioning

confidence: 99%

A Cloud Theory-Based Trust Computing Model in Social Networks

Liu

Zhu

et al. 2016

Entropy

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How to develop a trust management model and then to efficiently control and manage nodes is an important issue in the scope of social network security. In this paper, a trust management model based on a cloud model is proposed. The cloud model uses a specific computation operator to achieve the transformation from qualitative concepts to quantitative computation. Additionally, this can also be used to effectively express the fuzziness, randomness and the relationship between them of the subjective trust. The node trust is divided into reputation trust and transaction trust. In addition, evaluation methods are designed, respectively. Firstly, the two-dimension trust cloud evaluation model is designed based on node's comprehensive and trading experience to determine the reputation trust. The expected value reflects the average trust status of nodes. Then, entropy and hyper-entropy are used to describe the uncertainty of trust. Secondly, the calculation methods of the proposed direct transaction trust and the recommendation transaction trust involve comprehensively computation of the transaction trust of each node. Then, the choosing strategies were designed for node to trade based on trust cloud. Finally, the results of a simulation experiment in P2P network file sharing on an experimental platform directly reflect the objectivity, accuracy and robustness of the proposed model, and could also effectively identify the malicious or unreliable service nodes in the system. In addition, this can be used to promote the service reliability of the nodes with high credibility, by which the stability of the whole network is improved.

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Evaluation Approach of Subjective Trust Based on Cloud Model

Abstract: ABSTRACT

Cited by 36 publications

References 10 publications

A Trust-Based Agent Learning Model for Service Composition in Mobile Cloud Computing Environments

A Trust-Based Agent Learning Model for Service Composition in Mobile Cloud Computing Environments

Trust Models in Cloud Computing: A Review

A Cloud Theory-Based Trust Computing Model in Social Networks

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