Evolutionary trust scheme of certificate game in mobile cloud computing

Li, Dazhi; Li, Minglu; Liu, Jian Hua

doi:10.1007/s00500-017-2486-x

Cited by 10 publications

(5 citation statements)

References 33 publications

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“…In order to verify the authenticity of the above three scenarios, this study uses MATLAB R2021a software to simulate and analyze each parameter. Although the setting of the initial value of the parameter affects its evolution range and speed to a certain extent, it will not change its overall trend and results [54,55]. The most important thing is the accuracy of the model establishment and the practicality of the model, which aims to reveal the regular characteristics of things changing [56].…”

Section: Experimental Data and Simulationmentioning

confidence: 99%

Cooperative protection of technical secrets in cultural industry cluster-based on evolutionary game model of leading enterprises and following enterprises

Xu,

2023

PLoS ONE

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Due to the confidentiality, value and exclusivity of technical secrets, how to protect the technical secrets within cultural industry clusters has become a paradoxical issue and a research hotspot. Focusing on the collaborative protection of technical secrets within cultural industry clusters, this paper analyzes the strategies of collaborative protection of technical secrets between leading enterprises and following enterprises based on evolutionary game theory, and uses dynamic evolution and simulation methods to identify key factors behind the strategy choices, which further enriches the evolutionary mechanism of collaborative protection, and expands the application scenarios of the theory of evolutionary game. As the research results show, the collaborative protection strategy of technical secrets within cultural industry clusters is feasible, the cost of collaborative protection, government subsidies, and compensation for collaborative deposits are key variables that determine the trend of the game. The government subsidy coefficient, the collaborative deposits, and the difference in the number of technology secrets are strongly sensitive factors underlying the mode of protection, while the synergistic benefits between firms are weakly sensitive factors. Therefore, this paper proposes that increasing government subsidies and collaborative deposits, and reducing the differences in the number of technical secrets among game subjects can promote enterprises to eliminate suspicion and increase their willingness to cooperate in protecting technical secrets.

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Section: Experimental Data and Simulationmentioning

confidence: 99%

Cooperative protection of technical secrets in cultural industry cluster-based on evolutionary game model of leading enterprises and following enterprises

Xu,

2023

PLoS ONE

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“…1 Encryption [21,76,55,25,26,65,28,29,30,31,66,34,7,79,90,40,91,42,74,59,44,45,46,47,60,87,50,51,81,52,53,93,83,54,61] 2 Authentication [22,63,64,32,33,67,68,69,35,70,41,57,43,71,72,75,48,49,…”

Section: # Solutionsmentioning

confidence: 99%

“…Time consumption [21,55,22,24,63,26,27,29,31,66,33,34,67,68,37,7,38,39,40,41,42,57,71,58,59,75,44,47,48,49,51,88] Communication overhead [24,64,65,32,66,33,67,68,36,7,91,85,86,41,56,42,57,71,58,75,49,…”

Section: Resources Usage Metricsmentioning

confidence: 99%

Privacy and data protection in mobile cloud computing: A systematic mapping study

2020

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As a result of a shift in the world of technology, the combination of ubiquitous mobile networks and cloud computing produced the mobile cloud computing (MCC) domain. As a consequence of a major concern of cloud users, privacy and data protection are getting substantial attention in the field. Currently, a considerable number of papers have been published on MCC with a growing interest in privacy and data protection. Along with this advance in MCC, however, no specific investigation highlights the results of the existing studies in privacy and data protection. In addition, there are no particular exploration highlights trends and open issues in the domain. Accordingly, the objective of this paper is to highlight the results of existing primary studies published in privacy and data protection in MCC to identify current trends and open issues. In this investigation, a systematic mapping study was conducted with a set of six research questions. A total of 1711 studies published from 2009 to 2019 were obtained. Following a filtering process, a collection of 74 primary studies were selected. As a result, the present data privacy threats, attacks, and solutions were identified. Also, the ongoing trends of data privacy exercise were observed. Moreover, the most utilized measures, research type, and contribution type facets were emphasized. Additionally, the current open research issues in privacy and data protection in MCC were highlighted. Furthermore, the results demonstrate the current state-of-the-art of privacy and data protection in MCC, and the conclusion will help to identify research trends and open issues in MCC for researchers and offer useful information in MCC for practitioners.

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“…Many prior research efforts have been conducted to address the privacy and security threats. In light of the growing privacy concerns in MCC, Li et al [78] proposed a certificate-aware framework for online access control systems, where users were compensated for their privacy certificate and operation disclosure and were motivated to present more certificate information. Au et al [16] provided an overview towards the mobile cloud privacy threats from different levels, such as information theft and data integrity breakage.…”

Section: Security and Privacy Preserving For Mobile Cloud Healthcarementioning

confidence: 99%

An Overview of Mobile Cloud Computing for Pervasive Healthcare

Wang

Jin

2019

IEEE Access

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Mobile devices, along with wearable sensors, allow patients to access healthcare services from anywhere at any time. The longstanding constraints of computational capability and storage space on mobile devices can be alleviated by outsourcing computation-or data-intensive tasks to remote cloud centers. Thus, mobile cloud computing (MCC) has been recognized as a promising approach to provide pervasive healthcare services to people in their daily life. As the development and adoption of MCC techniques in healthcare, new optimization strategies have been explored and studied to help mobile cloud healthcare services to be deployed in a more effective and efficient manner. In this survey, we demonstrate how MCC techniques have been extensively deployed in various healthcare applications and, specifically, describe the general architecture and design considerations one should take into account while designing an MCC for healthcare scenarios. Given a large number of factors that may affect the performance of the MCC and even result in catastrophic consequences in healthcare, this paper presents the state-of-the-art optimization methods on the MCC for meeting the diverse priorities and achieving the optimal tradeoff among multiple objectives. Finally, the security and privacy issues of the MCC in healthcare are also discussed. INDEX TERMS Mobile cloud computing, pervasive healthcare. optimization, offloading, security and privacy. NOMENCLATURE

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Evolutionary trust scheme of certificate game in mobile cloud computing

Cited by 10 publications

References 33 publications

Cooperative protection of technical secrets in cultural industry cluster-based on evolutionary game model of leading enterprises and following enterprises

Cooperative protection of technical secrets in cultural industry cluster-based on evolutionary game model of leading enterprises and following enterprises

Privacy and data protection in mobile cloud computing: A systematic mapping study

An Overview of Mobile Cloud Computing for Pervasive Healthcare

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