| 云计算环境下基于评价可信度的动态信任评估模型 |
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| 引用本文： | 张琳,饶凯莉,王汝传.云计算环境下基于评价可信度的动态信任评估模型[J].通信学报,2013,34(Z1):5-37. |
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| 作者姓名： | 张琳 饶凯莉 王汝传 |
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| 作者单位： | 1. 南京邮电大学 计算机学院，江苏 南京 210003；2. 江苏省无线传感网高技术研究重点实验室，江苏 南京 210003；
3. 南京邮电大学 宽带无线通信与传感网技术教育部重点实验室，江苏 南京 210003 |
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| 基金项目： | 国家自然科学基金资助项目(61170065, 61171053, 61203217, 61103195, 61201163, 61202354)；江苏省自然科学基金资助项目(BK2011755, BK2011072, BK2012436)；江苏省科技支撑计划(工业)基金资助项目(BE2011189, BE2012183, BE2012755)；省属高校自然科学研究重大基金资助项目(12KJA520002)；省属高校自然科学基金资助项目（13KJB520017）；南京邮电大学科研基金资助项目(NY212063)；江苏高校优势学科建设工程基金资助项目(yx002001) |
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| 摘 要： | 针对云用户如何选取可信的云服务提供商问题，提出了基于评价可信度的动态信任评估模型。该模型将云服务提供商的服务能力和云用户所需求的服务能力分别划分等级，有效地解决了云服务提供商服务能力动态变化对模型存在的潜在破坏问题。建立了信任度随时间窗变化的动态信任机制，在计算信誉度时，将用户的评价可信度作为其评价证据的可信权重，通过引入评价可信度和评价相似度提高了计算推荐行为可信度的准确率。仿真结果表明，该模型的评估结果更贴近云服务提供商的真实信任度，同时能有效抵御恶意云用户的攻击。
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| 关 键 词： | 服务等级 时间窗 评价可信度 推荐可信度 |
Dynamic trust evaluation model based on evaluation
credibility in cloud computing |
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| Lin ZHANG,Kai-li RAO,Ru-chuan WANG.Dynamic trust evaluation model based on evaluation
credibility in cloud computing[J].Journal on Communications,2013,34(Z1):5-37. |
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| Authors: | Lin ZHANG Kai-li RAO Ru-chuan WANG |
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| Affiliation: | 1. College of Computer, Nanjing University of Posts and Telecommunications, Nanjing 210003, China;2. High Technology Research Key Laboratory for Wireless Sensor Networks of Jiangsu Province, Nanjing 210003, China;3. Key Lab of Broadband Wireless Communication and Sensor Network Technology, Ministry of Education, Nanjing University of Posts and Telecommunications, Nanjing 210003, China |
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| Abstract: | Considering the problem that cloud users will select a trusted cloud service provider, a dynamic trust evalua-tion model based on evaluation credibility was proposed.This model divides the ability of cloud service provider and the one of the user's requirments into many ranks, which can effectively solve the potential damage caused by the dynamic change in the ability of cloud service providers. A dynamic mechanism of trust changing about time-window was estab-lished. During the calculation of credibility, the user's evaluation credibility was used as the trust weight. The calculating accuracy of the recommended behavior credibility was improved by introducing the evaluation credibility and evaluation similarity. Simulation results show that the model results are closer to the cloud service provider's actual trust value, and can resist the attack of malicious cloud users effectively. |
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| Keywords: | service rank time-window evaluation credibility recommendation credibility |
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