A hybrid trust model based on communication and social trust for vehicular social networks

IF 1.9 4区 计算机科学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS
Na Fan, Shuai Shen, C. Wu, J. Yao
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引用次数: 4

Abstract

Vehicular social networks are emerging hybrid networks that combine traditional vehicular networks and social networks, with two key types of nodes, that is, vehicles and drivers. Since vehicle behaviors are controlled or influenced by drivers, the trustworthiness of a vehicle node is essentially determined by its own communication behaviors and its driver’s social characteristics. Therefore, human factors should be considered in securing the communication in vehicular social networks. In this article, we propose a hybrid trust model that considers both communication trust and social trust. Within the proposed scheme, we first construct a communication trust model to quantify the trust value based on the interactions between vehicle nodes, and then develop a social trust model to measure the social trust based on the social characteristics of vehicle drivers. Based on these two trust models, we compute the combined trust assessment of a vehicle node in vehicular social networks. Extensive simulations show that the proposed hybrid trust model improves the accuracy in evaluating the trustworthiness of vehicle nodes and the efficiency of communication in vehicular social networks.
基于通信和社会信任的汽车社交网络混合信任模型
车载社交网络是一种新兴的混合网络,它结合了传统的车载网络和社交网络,具有两种关键类型的节点,即车辆和驾驶员。由于车辆行为受到驾驶员的控制或影响,因此车辆节点的可信度本质上取决于其自身的通信行为和驾驶员的社会特征。因此,在确保车辆社交网络中的通信安全时,应考虑人为因素。在本文中,我们提出了一个混合信任模型,该模型同时考虑了沟通信任和社会信任。在所提出的方案中,我们首先构建了一个通信信任模型,根据车辆节点之间的互动来量化信任值,然后开发了一个社会信任模型,基于车辆驾驶员的社会特征来衡量社会信任。基于这两个信任模型,我们计算了车辆社交网络中车辆节点的组合信任评估。大量仿真表明,所提出的混合信任模型提高了评估车辆节点可信度的准确性和车辆社交网络中的通信效率。
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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来源期刊
CiteScore
6.50
自引率
4.30%
发文量
94
审稿时长
3.6 months
期刊介绍: International Journal of Distributed Sensor Networks (IJDSN) is a JCR ranked, peer-reviewed, open access journal that focuses on applied research and applications of sensor networks. The goal of this journal is to provide a forum for the publication of important research contributions in developing high performance computing solutions to problems arising from the complexities of these sensor network systems. Articles highlight advances in uses of sensor network systems for solving computational tasks in manufacturing, engineering and environmental systems.
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