TBRS: A trust based recommendation scheme for vehicular CPS network
TBRS: A trust based recommendation scheme for vehicular CPS network
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TBRS：一种基于信任的车载 CPS 网络推荐方案
DOI：
10.1016/j.future.2018.09.002
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发表时间：
2019-03-01
影响因子：
7.5
通讯作者：
Zomaya, Albert Y.
中科院分区：
文献类型：
--
作者：
Liang, Wei;Long, Jing;Zomaya, Albert Y.
在复杂的车辆信息物理系统（CPS）网络环境中，存在基于信任的推荐方案，可以有效地过滤大部分虚假数据。然而，这些方案可能耗尽车辆网络资源，包括能量、计算能力和存储，导致网络中断。为了保证车载CPS网络中数据传输的实时性和安全性，提出了一种新的基于信任的推荐方案。（1）CPS网络中车载传感器节点的异构性，分析了正常节点和自私/恶意节点在移动性上的差异。此外，还设计了一种基于节点的位置亲密度和投递可信度的信任模型。该模型可以调整直接信任参数的权重系数，用于分析数据传输中的安全可信任务。（2）针对车载CPS中自私/恶意节点的攻击和节点稀疏性问题，提出了一种基于K近邻（KNN）协同计算的安全过滤算法。信任值的计算所提出的信任模型。利用基于协同计算的过滤算法过滤自私/恶意节点的虚假推荐信任值，大大降低了自私/恶意节点对车载CPS网络性能的干扰。信任值的协同计算和信任值推荐的方式使TBRS模型比以往的模型更安全可靠。实验结果表明，TBRS方案在传输速率、传输延迟和可靠性方面均优于现有方案，具有上级性能。此外，与其他算法相比，对非法窃听攻击的抵抗力平均提高了32.53%。(C)2018爱思唯尔B.V.保留所有权利。
In complex vehicular cyber physical systems (CPS) network environment, there exist trust-based recommendation schemes that could effectively filter most of the false data. Though, these schemes may exhaust vehicular network resources, including energy, computation ability, and storage, causing a network outage. To ensure real-time data transmission and security in a vehicular CPS network, a novel trust based recommendation scheme (TBRS) is proposed in this research. The main contributions presented in this paper are as follows: (1) The isomerism of vehicular sensor nodes in CPS networks, where the differences of mobility between normal nodes and selfish/malicious nodes are analyzed. Besides, a trust model is designed based on delivery credibility and position intimacy of nodes. This model can adjust the weight coefficient of direct trust parameters, which can be utilized to analyze the secure and trustable tasks in data transmission, and (2) To address attacks caused by selfish/malicious nodes and sparsity issues of nodes in vehicular CPS, a secure filtering algorithm based on K-Nearest Neighbor (KNN) cooperative computing is proposed. The trust value is calculated by the proposed trust model. The cooperative computing-based filtering algorithm is utilized to filter false recommendation trust values from selfish/malicious nodes, which greatly reduces interference of selfish/malicious nodes on the performance of vehicular CPS network. The way of calculating trust value cooperatively and recommend trust value makes the TBRS model more secure and reliable than previous ones. Experimental results show that the TBRS scheme is superior to the existing schemes in terms of delivery rate, transmission delay and reliability. Besides, the resistance against illegal eavesdropping attacks has increased by an average of 32.53% when compared to other algorithms. (C) 2018 Elsevier B.V. All rights reserved.