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首页> 外文期刊>Journal of computational science >A novel crowd evaluation method for security and trustworthiness of online social networks platforms based on signaling theory
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A novel crowd evaluation method for security and trustworthiness of online social networks platforms based on signaling theory

机译：基于信号理论的在线社交网络平台安全性和可信性人群评估新方法

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Along with the convenience provided by the open online social networks (OSNs) for the users, there are also many burning problems like insecure platform, untrustworthy information, malicious propagation, even illegal cheating. Especially, security and trustworthiness of social platforms, as the foundation of social interactions, plays an important role in active users' sharing and communication. The available research efforts of the aspects mainly focus on exploring security mechanisms and methods, as well as establishing trust relationship among social users. However, the evaluation and measurement for social platforms have not yet been well conducted.This paper proposed a novel method for crowd evaluating the security and trustworthiness of OSNs platforms based on signaling theory, which have been generally employed in the fields of economics and information management. Firstly, we classified the security and trust-critical signals of generic OSNs platform itself, and formalized static attributes and dynamic behaviors features by using the OWL and the temporal logic. Then, a comprehensive computational model for security and trustworthiness measurement was proposed inspired by crowd computing, after signals' weights were yielded based on Fuzzy Analytic Hierarchy Process Comprehensive Evaluation. Finally, the evaluation experiments were carried out by using crowd evaluation architecture on a real world multimedia social network platform called CyVOD MSN. The experimental results denote that the proposed approach can effectively achieve the assessments of every security and trust-critical signals of the social platforms, and further realize the functional evolution of CyVOD MSN through improving insecure and untrustworthy vulnerabilities found by the crowd evaluation. (C) 2017 Elsevier B.V. All rights reserved.
机译：除了开放的在线社交网络（OSN）为用户提供的便利之外，还存在许多迫在眉睫的问题，例如不安全的平台，不可靠的信息，恶意传播甚至非法作弊。尤其是，社交平台的安全性和可信赖性作为社交互动的基础，在活跃用户的共享和交流中起着重要作用。这些方面的可用研究工作主要集中在探索安全机制和方法，以及建立社交用户之间的信任关系。然而，对于社交平台的评估和测量还没有很好地进行。本文提出了一种基于信号理论的人群评估OSNs平台的安全性和可信度的新方法，该方法已广泛应用于经济和信息管理领域。 。首先，我们对通用OSN平台本身的安全和信任关键信号进行了分类，并通过使用OWL和时间逻辑来形式化了静态属性和动态行为特征。然后，在基于模糊层次分析法的综合评价得出信号权重后，提出了一种基于人群计算的安全与可信度测量综合计算模型。最后，使用人群评估架构在称为CyVOD MSN的现实世界多媒体社交网络平台上进行了评估实验。实验结果表明，所提出的方法可以有效地实现对社交平台的每个安全和信任关键信号的评估，并且可以通过改善人群评估中发现的不安全和不可信赖的漏洞，进一步实现CyVOD MSN的功能演进。 （C）2017 Elsevier B.V.保留所有权利。

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