Towards Trustworthy Participants in Social Participatory Networks

Guangquan Xu, Bin Liu, Yuanyuan Ren, Runhe Huang, Gaoxu Zhang, Zhiyong Feng, Xiaohong Li
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Abstract

By leveraging online social networks as an underlying infrastructure, Social Participatory Network (SPN) has been becoming a new paradigm of participatory sensing systems. However, a significant barrier to the widespread use of SPN applications is their vulnerability to various forms of malicious attacks. Such threats inhibit human participation and thus the viability of SPN systems in everyday use. To solve this problem, this paper proposes a trust evaluation framework for participants to encourage wider human participation in SPN. The proposal is based on the Tianjin University's own existing SPN system, named CRCS (ClassRoom Cloud System), which enables participants to use the cloud resources for online lessons or library study. It derives the trust value of participants by using entropy-weight method and data mining algorithms to deal with the behaviors data of participants. Our proposed solution can detect malicious participants easily, and more importantly, it outperforms other work for its low cost and simple deployment. For now, though our solution is based on a specified SPN system, we are confident that this solution is highly applicable to most other SPN systems.
社会参与网络中可信赖的参与者
通过利用在线社交网络作为底层基础设施,社会参与式网络(social Participatory Network, SPN)已成为参与式传感系统的新范式。然而,SPN应用程序广泛使用的一个重要障碍是它们容易受到各种形式的恶意攻击。这种威胁抑制了人类的参与,从而抑制了SPN系统在日常使用中的可行性。为了解决这一问题,本文提出了参与者的信任评估框架,以鼓励更广泛的人参与到SPN中。该提案基于天津大学现有的SPN系统,名为CRCS(课堂云系统),该系统使参与者能够使用云资源进行在线课程或图书馆学习。利用熵权法和数据挖掘算法对参与者的行为数据进行处理,得到参与者的信任值。该解决方案可以轻松检测恶意参与者,更重要的是其成本低,部署简单,优于其他工作。目前,尽管我们的解决方案基于特定的SPN系统,但我们确信该解决方案高度适用于大多数其他SPN系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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