现代电子技术2025，Vol.48Issue(11)：77-83,7.DOI:10.16652/j.issn.1004-373x.2025.11.012
车联网中可信隐私保护的恶意行为检测方案研究
Research on misbehavior detection scheme for trustworthy privacy protection in IoV
摘要
Abstract
Due to privacy leakage in centralized data centers,the detection of misbehavior attacks in the Internet of Vehicles(IoV)is hindered by the lack of real and up-to-date data,which in turn restricts the development of AI-based IoV misbehavior behavior detection.In view of the aforementioned,this study proposes a framework for misbehavior behavior detection in IoV that leverages federated learning and blockchain technology to protect privacy and reliability.The proposed framework is a distributed architecture based on edge servers,allowing multiple edge nodes to collaborate securely while preserving privacy.The framework also includes a trust management module based on blockchain technology,and this module is designed to maintain the reliability and credibility of the data used in the federated learning process within the IoV.The trust management module manages the trust data of each node,ensuring the integrity and reliability of the federated learning training process.This study utilized the VeReMi dataset for experiments.The experimental results show that the proposed framework has high misbehavior detection performance while protecting privacy.关键词
车联网/隐私保护/恶意行为检测/联邦学习/区块链/集中式/分布式/机器学习Key words
IoV/privacy protection/misbehavior detection/federated learning/blockchain/centralized/distributed/machine learning分类
信息技术与安全科学引用本文复制引用
江荣旺,梁志勇,龙草芳,杨明..车联网中可信隐私保护的恶意行为检测方案研究[J].现代电子技术,2025,48(11):77-83,7.基金项目
海南省重点研发项目(ZDYF2023GXJS007) （ZDYF2023GXJS007）
三亚学院校级项目(USYYB22-07) （USYYB22-07）
海南省教育厅重点科研项目(Hnky2023ZD-14) （Hnky2023ZD-14）
三亚学院重大专项课题(USY22XK-04) （USY22XK-04）
三亚学院人才项目(USYRC19-04) （USYRC19-04）
三亚学院产品思维导向特色课程改革项目(SYJKCP2023159) （SYJKCP2023159）
