A Metamodel for Measuring Accountability Attributes in the Cloud

Núñez, David; Fernández-Gago, Carmen; Pearson, Siani; Felici, Massimo De

doi:10.1109/cloudcom.2013.53

Cited by 15 publications

(16 citation statements)

References 6 publications

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“…The Cloud Accountability Project (A4Cloud) [6] focuses on the accountability of cloud services. As one of the key critical prerequisite, accountability is decomposed into several properties for effective control of services collaboration and governance of private data processed by cloud services.…”

Section: Related Workmentioning

confidence: 99%

A Trustworthiness Evaluation Framework in Cloud Computing for Service Selection

Wang

2014

2014 IEEE 6th International Conference on Cloud Computing Technology and Science

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Cloud computing provides many benefits for individuals and enterprises by offering a range of computing services. The service dynamism, elasticity, economy and choices are too attractive to ignore. At the meantime, cloud computing has opened up a new frontier of challenges by introducing trust scenario. The Trustworthiness Evaluation of cloud Services is a paramount concern. In this paper, we present a framework to quantitatively measure and rank the trustworthiness of cloud services. In particular, we address the fundamental understanding of trustworthiness, quantitative trustworthiness metrics, unified scale of trust factors, trust factors categorization, trust coordinate and multi-criteria analysis for trustworthiness decision making. Our comprehensive framework of trustworthiness evaluation contains five basic building blocks. The preprocessing block query and calculate the existent trustworthiness record. Then the trust factors are collected, if there was no match record found. The trust factor management block categorize the trust factors and convert them by using unified scale. The trust factor processing block is for weighting and positioning of trust factors. The trustworthiness decision making block provide calculation of cloud service trustworthiness, and the results are recorded in our trustworthiness record block. The proposed trustworthiness measurement framework is employed in several experiments by using existing trust dataset. The analysis based on the experiment result indicates our trustworthiness evaluation is accurate and flexible.

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Section: Related Workmentioning

confidence: 99%

A Trustworthiness Evaluation Framework in Cloud Computing for Service Selection

Wang

2014

2014 IEEE 6th International Conference on Cloud Computing Technology and Science

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“…The Cloud Accountability Project (A4Cloud) [4] focuses on the accountability of cloud services. As one of the key critical prerequisite, accountability is decomposed into several properties for effective control of services collaboration and governance of private data processed by cloud services.…”

Section: Related Workmentioning

confidence: 99%

“…We also define a function J for calculation of distance from trust vector to sphere center or contours. So we can calculate the evaluation rating using equation (4).…”

Section: ) Trust Vector Aggregationmentioning

confidence: 99%

A Novel Trustworthiness Measurement Model for Cloud Service

Wang

2014

2014 IEEE/ACM 7th International Conference on Utility and Cloud Computing

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Recent surveys show that there is enormous increase of organizations intending to adopt cloud, but one of their major obstructions is the trustworthiness evaluation of cloud service candidates. Performing evaluations of cloud service candidates is expensive and time consuming, especially with the breadth of services available today. In this situation, this paper proposes a novel trustworthiness measurement model to evaluate cloud service trustworthiness. By using the proposed trustworthiness measurement model, we first recognize and categorize trust factors in group of shared factors and unique factors. After special treatment of unique factors, all the trust factors in two groups are located in our designed trust dimension by different weighting and positioning approach. Then all the trust factors are converted to trust vectors, these various trust vectors of the services are considered by the designed multicriteria analysis mechanism which can help us to analyze trust features from different perspectives and provide a comprehensive trustworthiness evaluation. In case the measurement result is inconsistent with user preference, we also provide an adjustment approach based on knowledge learning to enhance the accuracy of measurement result. At the end of this paper, our designed trustworthiness measurement model is validated by several experiments. The experiments are designed based upon real world dataset and the results indicate the accuracy of our measurement can be guaranteed.

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“…In a similar way, some recent work on accountability in the cloud has started to emerge through projects such as A4CLOUD (http://www.a4cloud.eu), whereby researchers are trying to devise models that can help put in place the set of mechanisms that would ensure cloud providers are hold accountable should there be a breach of SLA or a security incident that can be traced back to a lax in their security. In the context of A4Cloud the concept of transparency in the broader sense is dealt with as an attribute of Accountability [42]. Readers interested in further comprehending the scope and diversity of existing efforts on SLA-based monitoring of cloud security can refer to the taxonomy of Petcu [43].…”

Section: Security Transparency Through Sla Managementmentioning

confidence: 99%

Security transparency: the next frontier for security research in the cloud

et al. 2015

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The recent advances in networking and the ubiquity of the Internet have enabled the emergence of cloud computing as a viable solution for a convenient, elastic and economical usage of services. In spite of these apparent advantages, the cloud model presents some challenges that hamper its wider adoption, most of which relate to security and privacy. This paper provides a review of the current initiatives devised by both academia and industry for addressing the security concerns inherent to the cloud model. Our analysis of the state of the art reveals that although initiatives such as SLA and virtual machines monitoring, and recent development in encryption mechanisms, have contributed to addressing some of the salient issues of security and privacy in the cloud, larger initiatives, other than standards, aiming at enabling security transparency and a mutual auditability in the cloud remain to be seen. With this in mind, the paper proposes some routes towards related solutions by discussing a number of desiderata for establishing a better security transparency between a Cloud Service Provider (CSP) and a Cloud Service Consumer (CSC). Given the current reluctance of some major businesses to embrace the trend, owing mainly to the devolution of some of the security aspects to a third party, the authors argue that undertaking some initiatives in that direction is a key to sustaining the current momentum of the cloud.

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A Metamodel for Measuring Accountability Attributes in the Cloud

Cited by 15 publications

References 6 publications

A Trustworthiness Evaluation Framework in Cloud Computing for Service Selection

A Trustworthiness Evaluation Framework in Cloud Computing for Service Selection

A Novel Trustworthiness Measurement Model for Cloud Service

Security transparency: the next frontier for security research in the cloud

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