Service Dynamic Trust Evaluation Model based on Bayesian Network in Distributed Computing Environment

Wang, Yunlong; Li, Xiangjun; Yan, Xinquan; Qing, Song; Chen, Yuanlu

doi:10.14257/ijsia.2015.9.5.03

Cited by 7 publications

(4 citation statements)

References 26 publications

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“…In reputations based systems [14], the most reputed users have the heaviest impact on the final trust value evaluated from the weighted sum method [48]. Other approaches described by Guo et al [36] include Bayesian Systems [49] [50] [51], Regression Analysis [52], Belief Models [53], Fuzzy Models [54] [55] [56] [57] [40] [58] [29], and Flow Models [59] [60] [61]. Bayesian systems and Fuzzy models are the two most widespread trust evaluation strategies.…”

Section: Trust Value Computation and Evaluation Strategiesmentioning

confidence: 99%

Trust Management in the World of Cloud Computing. Past Trends and Some New Directions

Saleem

Warsi

Islam

et al. 2021

SCPE

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Over the past years, Cloud computing has become one of the most influential information technologies to combat computing needs because of its unprecedented advantages. In spite of all the social and economic benefits it provides, it has its own fair share of issues. These include privacy, security, virtualization, storage, and trust. The underlying issues of privacy, security, and trust are the major barriers to the adoption of cloud by individuals and organizations as a whole. Trust has been the least looked into since it includes both subjective and objective characteristics. There is a lack of review on trust models in this research domain. This paper focuses on getting insight into the nomenclature of trust, its classifications, trust dimensions and throws an insight into various trust models that exist in the current knowledge stack. Also, various trust evaluation measures are highlighted in this work. We also draw a comparative analysis of various trust evaluation models and metrics to better understand the notion of trust in cloud environments. Furthermore, this work brings into light some of the gaps and areas that need to be tackled toward solving the trust issues in cloud environments so as to provide a trustworthy cloud ecosystem. Lastly, we proposed a Machine Learning backed Rich model based solution for trust verification in Cloud Computing. We proposed an approach for verifying whether the right software is running for the correct services in a trusted manner by analyzing features generated from the output cloud processed data. The proposed scheme can be utilized for verifying the cloud trust in delivering services as expected that can be perceived as an initiative towards trust evaluation in cloud services employing Machine learning techniques. The experimental results prove that the proposed method verifies the service utilized with an accuracy of 99%.

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Section: Trust Value Computation and Evaluation Strategiesmentioning

confidence: 99%

Trust Management in the World of Cloud Computing. Past Trends and Some New Directions

Saleem

Warsi

Islam

et al. 2021

SCPE

View full text Add to dashboard Cite

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“…is paper uses [23] to calculate the direct trust method to evaluate the risk of user interaction. We assume that there are m interactions between the user and the security domain.…”

Section: Risk Assessment Centermentioning

confidence: 99%

“…e number of successful interactions between user u and security domain d is S ud , and the number of user u failures with security domain d is F ud . It can be known from [23] that the risk probability θ e ∧ of the interaction between the user and the security domain conforms to the Beta distribution in the probability distribution. e calculation method is as follows:…”

Section: Risk Assessment Centermentioning

confidence: 99%

Risk Situation Assessment Model Based on Interdomain Interaction in Cloud Computing Environment

Wang

2020

Security and Communication Networks

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With the widespread application of cloud computing sharing technology, the demand for cross-domain interaction is also increasing. However, due to the uncertainty of interaction behaviour and the difference of network service quality, the risk of cross-domain interaction cannot be accurately evaluated. Therefore, this paper proposes a risk situation evaluation model based on interdomain interactions. The model collects interactive credentials such as the frequency, credibility, and time-effectiveness of the user-submitted evaluations. At the same time, it collects the evaluation of quality of service provided by the network security domain. Then, we set up a risk evaluation equation based on the interaction credentials to implement the risk evaluation of cross-domain interaction behaviour. Finally, we apply MATLAB platform to simulate the evolution process of evaluation. The experimental results show that, compared with other models, the evaluation method proposed in this paper improves the accuracy of the evaluation results and meets the security requirements of multidomain interaction.

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“…To do so, in this book chapter question number two has been split into two questions and struggles to answer these two questions which have been mention before. Figure 4 illustrates the components of common trust framework which is based on the [13].…”

Section: Evaluation Criteriamentioning

confidence: 99%

Evaluation Theory for Characteristics of Cloud Identity Trust Framework

Ghazizadeh¹,

Cusack²

2019

Cloud Computing - Technology and Practices

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Trust management is a prominent area of security in cloud computing because insufficient trust management hinders cloud growth. Trust management systems can help cloud users to make the best decision regarding the security, privacy, Quality of Protection (QoP), and Quality of Service (QoS). A Trust model acts as a security strength evaluator and ranking service for the cloud and cloud identity applications and services. It might be used as a benchmark to setup the cloud identity service security and to find the inadequacies and enhancements in cloud infrastructure. This chapter addresses the concerns of evaluating cloud trust management systems, data gathering, and synthesis of theory and data. The conclusion is that the relationship between cloud identity providers and Cloud identity users can greatly benefit from the evaluation and critical review of current trust models.

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Service Dynamic Trust Evaluation Model based on Bayesian Network in Distributed Computing Environment

Abstract: Abstract

Cited by 7 publications

References 26 publications

Trust Management in the World of Cloud Computing. Past Trends and Some New Directions

Trust Management in the World of Cloud Computing. Past Trends and Some New Directions

Risk Situation Assessment Model Based on Interdomain Interaction in Cloud Computing Environment

Evaluation Theory for Characteristics of Cloud Identity Trust Framework

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