A computational model to evaluate honesty in social internet of things

Upul Jayasinghe, Hyun-Woo Lee, G. Lee
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引用次数: 23

Abstract

Trust in Social Internet of Things has allowed to open new horizons in collaborative networking, particularly by allowing objects to communicate with their service providers, based on their relationships analogy to human world. However, strengthening trust is a challenging task as it involves identifying several influential factors in each domain of social-cyber-physical systems in order to build a reliable system. In this paper, we address the issue of understanding and evaluating honesty that is an important trust metric in trustworthiness evaluation process in social networks. First, we identify and define several trust attributes, which affect directly to the honesty. Then, a subjective computational model is derived based on experiences of objects and opinions from friendly objects with respect to identified attributes. Based on the outputs of this model a final honest level is predicted using regression analysis. Finally, the effectiveness of our model is tested using simulations.
社会物联网诚信评价的计算模型
对社交物联网的信任为协作网络开辟了新的视野,特别是允许对象基于与人类世界的关系类比与服务提供商进行通信。然而,增强信任是一项具有挑战性的任务,因为它涉及到在社会-网络-物理系统的每个领域中识别几个影响因素,以建立一个可靠的系统。在本文中,我们解决了理解和评估诚信的问题,这是一个重要的信任指标,在可信度评估过程中,社会网络。首先,我们识别并定义了几个直接影响诚信的信任属性。然后,基于对象的经验和友好对象关于识别属性的意见,推导出主观计算模型。基于该模型的输出,使用回归分析预测了最终的诚实水平。最后,通过仿真验证了模型的有效性。
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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