[1]田 钊,周 政,牛亚杰,等.基于区块链和时空特征融合的车联网信誉评估方法[J].郑州大学学报(工学版),2027,48(XX):1-8.[doi:10.13705/j.Issn.1671-6833.2026.06.008]
　TIAN Zhao,ZHOU Zheng,NIU Ya Jie,et al.A Reputation Assessment Method for Vehicular Networks Based on the Fusion of Spatiotemporal Features and Blockchain[J].Journal of Zhengzhou University (Engineering Science),2027,48(XX):1-8.[doi:10.13705/j.Issn.1671-6833.2026.06.008]
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基于区块链和时空特征融合的车联网信誉评估方法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
48
期数:
2027年XX
页码:
1-8
栏目:
出版日期:
2027-12-10

文章信息/Info

Title:
A Reputation Assessment Method for Vehicular Networks Based on the Fusion of Spatiotemporal Features and Blockchain
作者:
田 钊1,2，周 政1,2，牛亚杰1,2，鲁豪杰1,2，刘 炜1,2，宰光军1,2
1.郑州大学 网络空间安全学院 河南 郑州 450000;2.郑州市区块链与数据智能重点实验室 河南 郑州 450000;
Author(s):
TIAN Zhao1,2, ZHOU Zheng1,2, NIU Ya Jie 1,2, Lu Hao Jie1,2, LIU Wei1,2 ZAI Guang Jun1,2
1.School of Cyber Science and Engineering, Zhengzhou University, Zhengzhou 450000, China; 2.Zhengzhou Key Laboratory of Blockchain and Data IntelligenceZhengzhou 450000China;
关键词:
智能交通; 区块链; 人工智能; 车联网; 信誉评估
Keywords:
intelligent transportation;  blockchain;  artificial intelligence;  internet of vehicles;  reputation assessment
分类号:
TP389.1
DOI:
10.13705/j.Issn.1671-6833.2026.06.008
文献标志码:
A
摘要:
针对车联网中节点恶意攻击与自私行为导致交互数据不可信，且现有方法易引发信誉贬值的问题，提出一种基于区块链与时空特征融合的信誉评估方法。首先，引入高斯朴素贝叶斯算法融合时间与空间特征，旨在提高动态环境下信誉评估的准确性；其次，以事件确认度为依据更新信誉，实现更可靠的信誉聚合；最后，在智能合约中部署基于信令博弈的奖惩与税收机制，用于维持全局信誉动态平衡。仿真结果表明，本方法的识别精确度与召回率保持在82%和81%以上；面对高隐蔽性的恶意开关攻击，可在2.5分钟内将攻击节点信誉清零。该方法有效抑制了复杂网络攻击与理性自私行为，从机制上避免了系统信誉贬值，保障了车联网数据交互的安全。
Abstract:
Aiming at the problem of untrusted interaction data caused by malicious attacks and selfish behaviors of nodes in the Internet of Vehicles (IoV), and the issue that existing methods are prone to cause reputation depreciation, a reputation assessment method fusing blockchain and spatiotemporal features was proposed. First, the Gaussian Naive Bayes algorithm was introduced to fuse temporal and spatial features, aiming to improve the accuracy of reputation assessment in dynamic environments. Second, reputation was updated based on the event confirmation degree to achieve more reliable reputation aggregation. Finally, a reward and punishment mechanism and a taxation mechanism based on signaling games were deployed in smart contracts to maintain the dynamic balance of global reputation. Simulation results showed that the identification precision and recall of the proposed method remained above 82% and 81%, respectively. Facing highly concealed malicious switching attacks, it could reduce the reputation of attacking nodes to zero within 2.5 minutes. This method effectively suppressed complex network attacks and rational selfish behaviors, mechanically avoided system reputation depreciation, and guaranteed the security of data interaction in the IoV

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2026-04-29;修订日期:2026-05-28基金项目:河南省科技攻关项目 ( 252102210185) ;综合交通运输大数据应用技术交通运 输 行 业 重 点 实 验 室 开 放 课 题(2022B1201)作者简介:田 钊 ( 1985— ) ,男,郑 州 大 学 副 教 授,博 士,主 要 从 事 信 息 安 全、区 块 链、智 能 交 通 等 方 面 的 研 究, E-mail:tianzhao@ zzu. edu. cn。通讯作者:宰光军(1979— ) ,男,郑州大学副教授,主要从事信息安全、软件工程、金融信息系统等方面的研究,E-mail:zaiguangjun@ zzu. edu. cn。
更新日期/Last Update: 2026-06-03