{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,3]],"date-time":"2026-06-03T04:34:41Z","timestamp":1780461281199,"version":"3.54.1"},"reference-count":43,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2024,3,27]],"date-time":"2024-03-27T00:00:00Z","timestamp":1711497600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Research and Development Science and Technology of Hainan Province","award":["GHYF2022010"],"award-info":[{"award-number":["GHYF2022010"]}]},{"name":"Key Research and Development Science and Technology of Hainan Province","award":["RZ2100003340"],"award-info":[{"award-number":["RZ2100003340"]}]},{"name":"Key Research and Development Science and Technology of Hainan Province","award":["U1836210"],"award-info":[{"award-number":["U1836210"]}]},{"name":"Research Startup Foundation of Hainan University","award":["GHYF2022010"],"award-info":[{"award-number":["GHYF2022010"]}]},{"name":"Research Startup Foundation of Hainan University","award":["RZ2100003340"],"award-info":[{"award-number":["RZ2100003340"]}]},{"name":"Research Startup Foundation of Hainan University","award":["U1836210"],"award-info":[{"award-number":["U1836210"]}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["GHYF2022010"],"award-info":[{"award-number":["GHYF2022010"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["RZ2100003340"],"award-info":[{"award-number":["RZ2100003340"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U1836210"],"award-info":[{"award-number":["U1836210"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Connected Automobile Vehicles (CAVs) enable cooperative driving and traffic management by sharing traffic information between them and other vehicles and infrastructures. However, malicious vehicles create Sybil vehicles by forging multiple identities and sharing false location information with CAVs, misleading their decisions and behaviors. The existing work on defending against Sybil attacks has almost exclusively focused on detecting Sybil vehicles, ignoring the traceability of malicious vehicles. As a result, they cannot fundamentally alleviate Sybil attacks. In this work, we focus on tracking the attack source of malicious vehicles by using a novel detection mechanism that relies on vehicle broadcast beacon packets. Firstly, the roadside units (RSUs) randomly instruct vehicles to perform customized key broadcasting and listening within communication range. This allows the vehicle to prove its physical presence by broadcasting. Then, RSU analyzes the beacon packets listened to by the vehicle and constructs a neighbor graph between the vehicles based on the customized particular fields in the beacon packets. Finally, the vehicle\u2019s credibility is determined by calculating the edge success probability of vehicles in the neighbor graph, ultimately achieving the detection of Sybil vehicles and tracing malicious vehicles. The experimental results demonstrate that our scheme achieves the real-time detection and tracking of Sybil vehicles, with precision and recall rates of 98.53% and 95.93%, respectively, solving the challenge of existing detection schemes failing to combat Sybil attacks from the root.<\/jats:p>","DOI":"10.3390\/s24072153","type":"journal-article","created":{"date-parts":[[2024,3,27]],"date-time":"2024-03-27T13:39:56Z","timestamp":1711546796000},"page":"2153","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Sybil Attacks Detection and Traceability Mechanism Based on Beacon Packets in Connected Automobile Vehicles"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-2208-2959","authenticated-orcid":false,"given":"Yaling","family":"Zhu","sequence":"first","affiliation":[{"name":"The School of Cyberspace Security, Hainan University, Haikou 570208, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jia","family":"Zeng","sequence":"additional","affiliation":[{"name":"The School of Cyberspace Security, Hainan University, Haikou 570208, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fangchen","family":"Weng","sequence":"additional","affiliation":[{"name":"The School of Cyberspace Security, Hainan University, Haikou 570208, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dan","family":"Han","sequence":"additional","affiliation":[{"name":"The School of Cyberspace Security, Hainan University, Haikou 570208, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yiyu","family":"Yang","sequence":"additional","affiliation":[{"name":"The School of Cyberspace Security, Hainan University, Haikou 570208, China"},{"name":"The National Computer Intrusion Protection Center, University of Chinese Academy of Sciences, Beijing 101408, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6012-9178","authenticated-orcid":false,"given":"Xiaoqi","family":"Li","sequence":"additional","affiliation":[{"name":"The School of Cyberspace Security, Hainan University, Haikou 570208, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuqing","family":"Zhang","sequence":"additional","affiliation":[{"name":"The School of Cyberspace Security, Hainan University, Haikou 570208, China"},{"name":"The National Computer Intrusion Protection Center, University of Chinese Academy of Sciences, Beijing 101408, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,3,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Ali, G.M.N., Ayalew, B., Vahidi, A., and Noor-A-Rahim, M. (2019, January 22\u201325). Analysis of reliabilities under different path loss models in urban\/sub-urban vehicular networks. Proceedings of the 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), Honolulu, HI, USA.","DOI":"10.1109\/VTCFall.2019.8891389"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Sadaf, M., Iqbal, Z., Javed, A.R., Saba, I., Krichen, M., Majeed, S., and Raza, A. (2023). Connected and automated vehicles: Infrastructure, applications, security, critical challenges, and future aspects. Technologies, 11.","DOI":"10.3390\/technologies11050117"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Bari, B.S., Yelamarthi, K., and Ghafoor, S. (2023). Intrusion detection in vehicle controller area network (can) bus using machine learning: A comparative performance study. Sensors, 23.","DOI":"10.3390\/s23073610"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"493","DOI":"10.3390\/jcp3030025","article-title":"Autonomous vehicles: Sophisticated attacks, safety issues, challenges, open topics, blockchain, and future directions","volume":"3","author":"Giannaros","year":"2023","journal-title":"J. Cybersecur. Priv."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"e1515","DOI":"10.1002\/widm.1515","article-title":"Machine learning and blockchain technologies for cybersecurity in connected vehicles","volume":"14","author":"Ahmad","year":"2024","journal-title":"Wiley Interdiscip. Rev. Data Min. Knowl. Discov."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Sheik, A.T., Maple, C., Epiphaniou, G., and Dianati, M. (2023). A Comprehensive Survey of Threats in Platooning\u2014A Cloud-Assisted Connected and Autonomous Vehicle Application. Information, 15.","DOI":"10.3390\/info15010014"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Sheik, A.T., Maple, C., Epiphaniou, G., and Dianati, M. (2023). Securing Cloud-Assisted Connected and Autonomous Vehicles: An In-Depth Threat Analysis and Risk Assessment. Sensors, 24.","DOI":"10.3390\/s24010241"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"3614","DOI":"10.1109\/TITS.2023.3236274","article-title":"Autonomous vehicles security: Challenges and solutions using blockchain and artificial intelligence","volume":"24","author":"Bendiab","year":"2023","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_9","first-page":"287","article-title":"A review of attacks and their countermeasures in autonomous vehicles","volume":"13","author":"Jayanthi","year":"2023","journal-title":"IJCSPUB-Int. J. Curr. Sci. (IJCSPUB)"},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"90641","DOI":"10.1109\/ACCESS.2023.3307473","article-title":"An investigation of cyber-attacks and security mechanisms for connected and autonomous vehicles","volume":"11","author":"Gupta","year":"2023","journal-title":"IEEE Access"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Gupta, S., and Maple, C. (2023). A Survey of Security Mechanisms for Edge Computing based Connected Autonomous Vehicles. Authorea Preprints.","DOI":"10.36227\/techrxiv.20115317.v1"},{"key":"ref_12","unstructured":"Douceur, J.R. (2002, January 7\u20138). The sybil attack. Proceedings of the Peer-to-Peer Systems: First InternationalWorkshop, IPTPS 2002, Cambridge, MA, USA. Revised Papers 1."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Benadla, S., and Merad-Boudia, O.R. (2021, January 21\u201322). The impact of sybil attacks on vehicular fog networks. Proceedings of the 2021 International Conference on Recent Advances in Mathematics and Informatics (ICRAMI), Tebessa, Algeria.","DOI":"10.1109\/ICRAMI52622.2021.9585965"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"5597","DOI":"10.1109\/TVT.2022.3233624","article-title":"Efficient Detection and Localization of DoS Attacks in Heterogeneous Vehicular Networks","volume":"72","author":"Dey","year":"2023","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"142846","DOI":"10.1109\/ACCESS.2023.3343405","article-title":"Zero-Knowledge Proof of Traffic: A Deterministic and Privacy-Preserving Cross Verification Mechanism for Cooperative Perception Data","volume":"11","author":"Tao","year":"2023","journal-title":"IEEE Access"},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zhong, Y., Yang, H., Li, Y., Yang, B., Li, X., Yue, Q., Hu, J., and Zhang, Y. (2023, January 16\u201318). Sybil Attack Detection in VANETs: An LSTM-Based BiGAN Approach. Proceedings of the 2023 International Conference on Data Security and Privacy Protection (DSPP), Xi\u2019an, China.","DOI":"10.1109\/DSPP58763.2023.10404993"},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Verchok, N., and Orailo\u011flu, A. (2020, January 5\u20139). Hunting Sybils in Participatory Mobile Consensus-Based Networks. Proceedings of the 15th ACM Asia Conference on Computer and Communications Security, Taipei, Taiwan.","DOI":"10.1145\/3320269.3372200"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Faisal, S.M., Gupta, B.K., and Zaidi, T. (2022, January 26\u201327). A hybrid framework to prevent VANET from Sybil Attack. Proceedings of the 2022 5th International Conference on Multimedia, Signal Processing and Communication Technologies (IMPACT), Aligarh, India.","DOI":"10.1109\/IMPACT55510.2022.10029103"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Lim, K., Islam, T., Kim, H., and Joung, J. (2020, January 10\u201313). A Sybil attack detection scheme based on ADAS sensors for vehicular networks. Proceedings of the 2020 IEEE 17th Annual Consumer Communications & Networking Conference (CCNC), Las Vegas, NV, USA.","DOI":"10.1109\/CCNC46108.2020.9045356"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Kamel, J., Haidar, F., Jemaa, I.B., Kaiser, A., Lonc, B., and Urien, P. (2019, January 10\u201312). A misbehavior authority system for sybil attack detection in c-its. Proceedings of the 2019 IEEE 10th Annual Ubiquitous Computing, Electronics & Mobile Communication Conference (UEMCON), New York City, NY, USA.","DOI":"10.1109\/UEMCON47517.2019.8993045"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"89499","DOI":"10.1109\/ACCESS.2022.3200703","article-title":"An Edge Based Attack Detection Model (EBAD) for Increasing the Trustworthiness in IoT Enabled Smart City Environment","volume":"10","author":"Minu","year":"2022","journal-title":"IEEE Access"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Yang, H., Zhong, Y., Yang, B., Yang, Y., Xu, Z., Wang, L., and Zhang, Y. (2022, January 27\u201330). An overview of sybil attack detection mechanisms in vfc. Proceedings of the 2022 52nd Annual IEEE\/IFIP International Conference on Dependable Systems and Networks Workshops (DSN-W), Baltimore, MD, USA.","DOI":"10.1109\/DSN-W54100.2022.00028"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Zhang, Z., Lai, Y., Chen, Y., Wei, J., and Feng, Y. (2024, January 06). A Real-Time Detection Method for Sybil Attacks with High Traceability. Available online: https:\/\/ssrn.com\/abstract=4511059.","DOI":"10.2139\/ssrn.4511059"},{"key":"ref_24","unstructured":"Yuan, M., Lin, L., Wu, Z., and Ye, X. (2019). A novel sybil attack detection scheme based on edge computing for mobile iot environment. arXiv."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"e4621","DOI":"10.1002\/dac.4621","article-title":"A collaborative strategy for detection and eviction of Sybil attacker and Sybil nodes in VANET","volume":"34","author":"Krishnan","year":"2021","journal-title":"Int. J. Commun. Syst."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"75179","DOI":"10.1109\/ACCESS.2023.3294469","article-title":"LCSS Based Sybil Attack Detection and Avoidance in Clustered Vehicular Networks","volume":"11","author":"Rakhi","year":"2023","journal-title":"IEEE Access"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"109608","DOI":"10.1016\/j.comnet.2023.109608","article-title":"MDFD: A multi-source data fusion detection framework for Sybil attack detection in VANETs","volume":"224","author":"Chen","year":"2023","journal-title":"Comput. Netw."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"5403","DOI":"10.1109\/TVT.2020.2977829","article-title":"Fbia: A fog-based identity authentication scheme for privacy preservation in internet of vehicles","volume":"69","author":"Song","year":"2020","journal-title":"IEEE Trans. Veh. Technol."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Santhosh, J., and Sankaran, S. (2019, January 16\u201319). Defending against sybil attacks in vehicular platoons. Proceedings of the 2019 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), Goa, India.","DOI":"10.1109\/ANTS47819.2019.9117945"},{"key":"ref_30","first-page":"1137","article-title":"An improved RSU-based authentication scheme for VANET","volume":"21","author":"Cheng","year":"2020","journal-title":"J. Internet Technol."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hicks, C., and Garcia, F.D. (2020, January 7\u201311). A vehicular DAA scheme for unlinkable ECDSA pseudonyms in V2X. Proceedings of the 2020 IEEE European Symposium on Security and Privacy (EuroS&P), Genoa, Italy.","DOI":"10.1109\/EuroSP48549.2020.00036"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"3775","DOI":"10.1109\/JIOT.2019.2892009","article-title":"BLA: Blockchain-assisted lightweight anonymous authentication for distributed vehicular fog services","volume":"6","author":"Yao","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_33","first-page":"100228","article-title":"An efficient conditional privacy-preserving authentication scheme for Vehicle-To-Infrastructure communication in VANETs","volume":"22","author":"Ali","year":"2020","journal-title":"Veh. Commun."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Haddaji, A., Ayed, S., and Fourati, L.C. (January, January 29). Blockchain-based multi-levels trust mechanism against sybil attacks for vehicular networks. Proceedings of the 2020 IEEE 14th International Conference on Big Data Science and Engineering (BigDataSE), Guangzhou, China.","DOI":"10.1109\/BigDataSE50710.2020.00028"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1149","DOI":"10.1007\/s11277-020-07272-8","article-title":"An effective privacy-aware Sybil attack detection scheme for secure communication in vehicular ad hoc network","volume":"113","author":"Parham","year":"2020","journal-title":"Wirel. Pers. Commun."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1215","DOI":"10.1109\/TCC.2020.2985050","article-title":"Malicious node detection scheme based on correlation of data and network topology in fog computing-based VANETs","volume":"10","author":"Gu","year":"2020","journal-title":"IEEE Trans. Cloud Comput."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"172","DOI":"10.17148\/IARJSET.2017.4631","article-title":"Segregation of Sybil Attack using Neighbouring Information in VANET","volume":"4","author":"Panchal","year":"2017","journal-title":"Int. Adv. Res. J. Sci. Eng. Technol. ISSN"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Yujia, H., Yongfeng, H., and Fu, C. (2020, January 16\u201318). Research on node authentication of MQTT protocol. Proceedings of the 2020 IEEE 11th International Conference on Software Engineering and Service Science (ICSESS), Beijing, China.","DOI":"10.1109\/ICSESS49938.2020.9237678"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"6567","DOI":"10.1007\/s12652-020-02276-5","article-title":"Novel Sybil attack detection using RSSI and neighbour information to ensure secure communication in WSN","volume":"12","author":"Angappan","year":"2021","journal-title":"J. Ambient Intell. Humaniz. Comput."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"3919","DOI":"10.1109\/TNSM.2022.3216073","article-title":"Detecting Sybil Attacks in Vehicular Fog Networks Using RSSI and Blockchain","volume":"19","author":"Benadla","year":"2022","journal-title":"IEEE Trans. Netw. Serv. Manag."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"103092","DOI":"10.1016\/j.adhoc.2023.103092","article-title":"Detection method to eliminate Sybil attacks in Vehicular Ad-hoc Networks","volume":"141","author":"Zhang","year":"2023","journal-title":"Ad Hoc Netw."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"643","DOI":"10.1177\/0037549707085632","article-title":"Experimental evaluation of wireless simulation assumptions","volume":"83","author":"Newport","year":"2007","journal-title":"Simulation"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1109\/TMC.2010.133","article-title":"Bidirectionally coupled network and road traffic simulation for improved IVC analysis","volume":"10","author":"Sommer","year":"2010","journal-title":"IEEE Trans. Mob. Comput."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/7\/2153\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T14:19:40Z","timestamp":1760105980000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/24\/7\/2153"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,3,27]]},"references-count":43,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2024,4]]}},"alternative-id":["s24072153"],"URL":"https:\/\/doi.org\/10.3390\/s24072153","relation":{},"ISSN":["1424-8220"],"issn-type":[{"value":"1424-8220","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,3,27]]}}}