{"title":"使用恶意感知多重路由的 VANET 信任模型","authors":"Xiaorui Dang , Guiqi Zhang , Ke Sun , Yufeng Li","doi":"10.1016/j.cose.2024.104145","DOIUrl":null,"url":null,"abstract":"<div><div>Vehicular ad hoc networks (VANETs) enable multi-hop communication among vehicles, promoting information sharing and smarter collaborative driving. However, VANETs are facing several challenges due to the open wireless communication environment. Attackers may maliciously drop or alter packets so that the receiver cannot obtain correct information. In addition, the high mobility of vehicles may lead to link failures, consequently resulting in packet loss. In this paper, we propose a multipath-based trust model (MPTM), in which the reliability of packet transmission is guaranteed by data redundancy and the detection of potential attackers is achieved by trust evaluation. Specifically, we present a route discovery mechanism to find multiple routes that avoid potential attackers, which reduces the risk of attacks on redundant packets. The receivers identify correct information based on two factors including content consistency and route information. An attacker detection module is presented to evaluate the trustworthiness of vehicles involved in packet transmission and vehicles with trust value below a threshold are detected as attackers. We conducted extensive experiments using OMNeT++ simulation platform, considering various attack scenarios. Experiment results show that MPTM can reach 90% packet delivery ratio and effectively detect attackers in terms of 90% detection precision.</div></div>","PeriodicalId":51004,"journal":{"name":"Computers & Security","volume":"148 ","pages":"Article 104145"},"PeriodicalIF":4.8000,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A trust model for VANETs using malicious-aware multiple routing\",\"authors\":\"Xiaorui Dang , Guiqi Zhang , Ke Sun , Yufeng Li\",\"doi\":\"10.1016/j.cose.2024.104145\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Vehicular ad hoc networks (VANETs) enable multi-hop communication among vehicles, promoting information sharing and smarter collaborative driving. However, VANETs are facing several challenges due to the open wireless communication environment. Attackers may maliciously drop or alter packets so that the receiver cannot obtain correct information. In addition, the high mobility of vehicles may lead to link failures, consequently resulting in packet loss. In this paper, we propose a multipath-based trust model (MPTM), in which the reliability of packet transmission is guaranteed by data redundancy and the detection of potential attackers is achieved by trust evaluation. Specifically, we present a route discovery mechanism to find multiple routes that avoid potential attackers, which reduces the risk of attacks on redundant packets. The receivers identify correct information based on two factors including content consistency and route information. An attacker detection module is presented to evaluate the trustworthiness of vehicles involved in packet transmission and vehicles with trust value below a threshold are detected as attackers. We conducted extensive experiments using OMNeT++ simulation platform, considering various attack scenarios. Experiment results show that MPTM can reach 90% packet delivery ratio and effectively detect attackers in terms of 90% detection precision.</div></div>\",\"PeriodicalId\":51004,\"journal\":{\"name\":\"Computers & Security\",\"volume\":\"148 \",\"pages\":\"Article 104145\"},\"PeriodicalIF\":4.8000,\"publicationDate\":\"2024-10-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers & Security\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167404824004504\",\"RegionNum\":2,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers & Security","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167404824004504","RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
A trust model for VANETs using malicious-aware multiple routing
Vehicular ad hoc networks (VANETs) enable multi-hop communication among vehicles, promoting information sharing and smarter collaborative driving. However, VANETs are facing several challenges due to the open wireless communication environment. Attackers may maliciously drop or alter packets so that the receiver cannot obtain correct information. In addition, the high mobility of vehicles may lead to link failures, consequently resulting in packet loss. In this paper, we propose a multipath-based trust model (MPTM), in which the reliability of packet transmission is guaranteed by data redundancy and the detection of potential attackers is achieved by trust evaluation. Specifically, we present a route discovery mechanism to find multiple routes that avoid potential attackers, which reduces the risk of attacks on redundant packets. The receivers identify correct information based on two factors including content consistency and route information. An attacker detection module is presented to evaluate the trustworthiness of vehicles involved in packet transmission and vehicles with trust value below a threshold are detected as attackers. We conducted extensive experiments using OMNeT++ simulation platform, considering various attack scenarios. Experiment results show that MPTM can reach 90% packet delivery ratio and effectively detect attackers in terms of 90% detection precision.
期刊介绍:
Computers & Security is the most respected technical journal in the IT security field. With its high-profile editorial board and informative regular features and columns, the journal is essential reading for IT security professionals around the world.
Computers & Security provides you with a unique blend of leading edge research and sound practical management advice. It is aimed at the professional involved with computer security, audit, control and data integrity in all sectors - industry, commerce and academia. Recognized worldwide as THE primary source of reference for applied research and technical expertise it is your first step to fully secure systems.