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浙江大学学报(工学版)
浙江大学学报(工学版)  2023, Vol. 57 Issue (4): 760-772    DOI: 10.3785/j.issn.1008-973X.2023.04.014
自动化技术、计算机技术     
区块链架构下具有隐私保护的车联网信誉模型
王传华1(),张权1,王慧敏3,徐欣1,*(),麻瓯勃2
1. 杭州电子科技大学 计算机与软件学院，浙江 杭州 310018
2. 浙江大学 计算机科学与技术学院，浙江 杭州 310027
3. 杭州师范大学 信息科学与技术学院，浙江 杭州 311121
Reputation model for VANETs with privacy-preserving under blockchain architecture
Chuan-hua WANG1(),Quan ZHANG1,Hui-min WANG3,Xin XU1,*(),Ou-bo MA2
1. Computer and Software School, Hangzhou Dianzi University, Hangzhou 310018, China
2. College of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China
3. School of Information Science and Technology, Hangzhou Normal University, Hangzhou 311121, China
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摘要：

针对车联网传统信誉机制存在的集中式信誉服务器不可信、威胁用户隐私及检测范围单一等问题，提出区块链架构下具有隐私保护的车联网信誉模型. 基于区块链技术，设计分布式可信的车联网信誉更新模型. 采用多密钥全同态加密算法实现评价数据的加密与计算，降低用户隐私泄露的风险. 设计回溯时间间隔自适应调整策略，防止恶意车辆基于信誉更新特性绕过检测. 仿真结果表明，该方案能够有效地保护用户隐私，对不同环境下的恶意车辆都能够保持较高的检测率和较低的误报率. 与传统方案相比，该方案针对车辆恶意行为的检出率提高了32%.
关键词： 车联网(VANETs);  隐私保护;  区块链;  信誉模型    
Abstract:

A reputation model for VANETs with privacy-preserving under the blockchain architecture was proposed aiming at the problems of the traditional reputation mechanism in vehicular Ad-hoc networks (VANETs), such as the untrustworthy centralized reputation server, the threat to users’ privacy and the single detection scope. A distributed and trusted reputation update model for VANETs was designed based on blockchain technology. The multi-key fully homomorphic encryption algorithm was used to realize the encryption and calculation of evaluation data and reduce the risk of user privacy leakage. An adaptive adjustment strategy for the backtracking time interval was designed to prevent malicious vehicles from bypassing detection based on the update characteristics of reputation. Simulation results show that the scheme can effectively protect user privacy, and can maintain a high detection rate and a low false positive rate for malicious vehicles in different environments. The detection rate of vehicle malicious behavior in this scheme was increased by 32% compared with the traditional scheme.
Key words: vehicular Ad-hoc networks (VANETs)    privacy-preserving    blockchain    reputation model
收稿日期: 2022-10-11 出版日期: 2023-04-21
CLC:  TP 393  
通讯作者: 徐欣     E-mail: wangchuanhua12@163.com;xuxin@akey.me
作者简介: 王传华（1996—），男，博士生，从事车联网安全的研究. orcid.org/0000-0002-1515-5860. E-mail： wangchuanhua12@163.com
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引用本文:

王传华,张权,王慧敏,徐欣,麻瓯勃. 区块链架构下具有隐私保护的车联网信誉模型[J]. 浙江大学学报(工学版), 2023, 57(4): 760-772.

Chuan-hua WANG,Quan ZHANG,Hui-min WANG,Xin XU,Ou-bo MA. Reputation model for VANETs with privacy-preserving under blockchain architecture. Journal of ZheJiang University (Engineering Science), 2023, 57(4): 760-772.

链接本文:

https://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2023.04.014    或    https://www.zjujournals.com/eng/CN/Y2023/V57/I4/760

图 1  车联网的信誉更新模型
图 2  车辆信誉的波动轨迹
图 3  车辆间的位置分布
图 4  车辆信誉评价的计算流程
图 5  区块链的存储结构
方案 信誉更新来源 核心算法 信誉更新方式 抵御攻击
文献[11]方案 历史数据、直接交互 0-1编码、FNV hash 中心数据库 链接攻击、假消息攻击
文献[13]方案 直接交互 分布式k-匿名 区块链 假消息攻击、开关攻击
文献[15]方案 直接交互、信任可靠度 加法同态 路侧单元 假消息攻击、合谋攻击
文献[20]方案 直接交互 — 区块链 假消息攻击
文献[17]方案 直接交互 Paillier[23] 中心云 自私行为、假消息攻击
本文方案 历史数据、直接交互、参数风险、信任可靠度 DT-PKC 区块链 链接攻击、自私行为、开关攻击、
合谋攻击、假消息攻击
表 1  与其他车联网信誉更新模型的比较
图 6  模拟街道地图
参数 数值
模拟面积/（km×km） 3.0×3.0
仿真时间/s 300
R2V通信距离/m 800
V2V通信距离/m 400
道路行驶车辆数 [30, 300]
平均速度/（km·h?1） [20, 120]
恶意车辆比例/% [0, 35]
初始信誉 0.6
表 2  车辆通信场景的模拟仿真参数
图 7  不同车辆密度下的检测性能
图 8  不同车速下的检测性能
图 9  不同恶意车辆比例下的检测性能
图 10  针对恶意车辆不同攻击行为的检测性能
图 11  智能恶意车辆的检测性能
图 12  不同恶意节点比例下的误报率
图 13  不同实体的计算时间开销
图 14  信誉更新的整体时间开销
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