Data-Driven and Feedback-Enhanced Trust Computing Pattern for Large-Scale Multi-Cloud Collaborative Services

Xiao-yong, LI; Ma, Huadóng; Yao, Wenbin; Gui, Xiaolin

doi:10.1109/tsc.2015.2475743

Cited by 35 publications

(18 citation statements)

References 21 publications

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“…An efficient pay-on-demand pricing strategy for streaming big data processing in multi-cloud environment was proposed in [106], to offer a low price for data load processing, while maximizing the revenues of cloud service providers. As for building trust across multiple cloud centers that collaborate together on data storage and processing, Li et al in [107] proposed a trust-aware monitoring architecture between users and cloud centers with hierarchical feedback mechanism to enhance the robustness and reliability of the quality of service of cloud providers, which helps provide them with a rating based on their trust reputation. This allows users to select services from different cloud providers based on feedback and past service records.…”

Section: B Multi-cloud Data Processingmentioning

confidence: 99%

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

et al. 2018

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The world is witnessing an unprecedented growth of cyber-physical systems (CPS), which are foreseen to revolutionize our world via creating new services and applications in a variety of sectors such as environmental monitoring, mobilehealth systems, intelligent transportation systems and so on. The information and communication technology (ICT) sector is experiencing a significant growth in data traffic, driven by the widespread usage of smartphones, tablets and video streaming, along with the significant growth of sensors deployments that are anticipated in the near future. It is expected to outstandingly increase the growth rate of raw sensed data. In this paper, we present the CPS taxonomy via providing a broad overview of data collection, storage, access, processing and analysis. Compared with other survey papers, this is the first panoramic survey on big data for CPS, where our objective is to provide a panoramic summary of different CPS aspects. Furthermore, CPS require cybersecurity to protect them against malicious attacks and unauthorized intrusion, which become a challenge with the enormous amount of data that is continuously being generated in the network. Thus, we also provide an overview of the different security solutions proposed for CPS big data storage, access and analytics. We also discuss big data meeting green challenges in the contexts of CPS.

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Section: B Multi-cloud Data Processingmentioning

confidence: 99%

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

et al. 2018

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“…The trust mechanism is an important element in any network computing environment [27][28][29][30][31][32][33]. There are many advantages to introducing a trust mechanism in clustered WSNs [16][17][18][19][20] and selecting a CH to detect failed or malicious nodes in the cluster [34].…”

Section: Challenges and Motivations Of This Workmentioning

confidence: 99%

Fast, Resource-Saving, and Anti-Collaborative Attack Trust Computing Scheme Based on Cross-Validation for Clustered Wireless Sensor Networks

Liu

2020

Sensors

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The trust computing mechanism has an increasing role in the cooperative work of wireless sensor networks. However, the computing speed, resource overhead, and anti-collaborative attack ability of a trust mechanism itself are three key challenging issues for any open and resource-constrained wireless sensor networks. In this study, we propose a fast, resource-saving, and anti-collaborative attack trust computing scheme (FRAT) based on across-validation mechanism for clustered wireless sensor networks. First, according to the inherent relationship among three network entities (which are made up of three types of network nodes, namely base stations, cluster heads, and cluster members), we propose the cross-validation mechanism, which is effective and reliable against collaborative attacks caused by malicious nodes. Then, we adopt a fast and resource-saving trust computing scheme for cooperation between between cluster heads or cluster members. This scheme is suitable for wireless sensor networks because it facilitates resource-saving. Through theoretical analysis and experiments, the feasibility and effectiveness of the trust computing scheme proposed in this study are verified.

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“…Focusing on above issues of trust evaluation in social media and on the basis of previous work on trustworthiness evaluation [4], [6], [14]- [16], this study presents an innovative trustworthiness evaluation mechanism based on human cognitive behavior. Multiple criteria are incorporated to reflect the characteristics of complexity and uncertainty of trust.…”

Section: B Our Contributionsmentioning

confidence: 99%

“…Trust management and computing systems are successfully used in numerous application scenarios, helping consumers identify trustworthy and reliable service providers [13], [16], [25]. Similar approaches are needed to support social media systems in identifying trustworthy information sources.…”

Section: Related Workmentioning

confidence: 99%

Info-Trust: A Multi-Criteria and Adaptive Trustworthiness Calculation Mechanism for Information Sources

Gao

et al. 2019

IEEE Access

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Social media have become increasingly popular for the sharing and spreading of user-generated content due to their easy access, fast dissemination, and low cost. Meanwhile, social media also enable the wide propagation of cyber frauds, which leverage fake information sources to reach an ulterior goal. The prevalence of untrustworthy information sources on social media can have significant negative societal effects. In a trustworthy social media system, trust calculation technology has become a key demand for the identification of information sources. Trust, as one of the most complex concepts in network communities, has multi-criteria properties. However, the existing work only focuses on single trust factor, and does not consider the complexity of trust relationships in social computing completely. In this paper, a multi-criteria trustworthiness calculation mechanism called Info-Trust is proposed for information sources, in which identity-based trust, behavior-based trust, relation-based trust, and feedback-based trust factors are incorporated to present an accuracy-enhanced full view of trustworthiness evaluation of information sources. More importantly, the weights of these factors are dynamically assigned by the ordered weighted averaging and weighted moving average (OWA-WMA) combination algorithm. This mechanism surpasses the limitations of existing approaches in which the weights are assigned subjectively. The experimental results based on the real-world datasets from Sina Weibo demonstrate that the proposed mechanism achieves greater accuracy and adaptability in trustworthiness identification of the network information. INDEX TERMS Multi-criteria, adaptive weight, trust calculation mechanism, information sources, social media.

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Data-Driven and Feedback-Enhanced Trust Computing Pattern for Large-Scale Multi-Cloud Collaborative Services

Cited by 35 publications

References 21 publications

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

Big Data Meet Cyber-Physical Systems: A Panoramic Survey

Fast, Resource-Saving, and Anti-Collaborative Attack Trust Computing Scheme Based on Cross-Validation for Clustered Wireless Sensor Networks

Info-Trust: A Multi-Criteria and Adaptive Trustworthiness Calculation Mechanism for Information Sources

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