{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T11:45:03Z","timestamp":1778759103258,"version":"3.51.4"},"reference-count":39,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T00:00:00Z","timestamp":1635811200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001871","name":"Funda\u00e7\u00e3o para a Ci\u00eancia e Tecnologia","doi-asserted-by":"publisher","award":["UIDB\/00319\/2020"],"award-info":[{"award-number":["UIDB\/00319\/2020"]}],"id":[{"id":"10.13039\/501100001871","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Information"],"abstract":"<jats:p>Vehicular Ad hoc Networks (VANETs) are an emerging type of network that increasingly encompass a larger number of vehicles. They are the basic support for Intelligent Transportation Systems (ITS) and for establishing frameworks which enable communication among road entities and foster the development of new applications and services aimed at enhancing driving experience and increasing road safety. However, VANETs\u2019 demanding characteristics make it difficult to implement security mechanisms, creating vulnerabilities easily explored by attackers. The main goal of this work is to propose an Intelligent Hierarchical Security Framework for VANET making use of Machine Learning (ML) algorithms to enhance attack detection, and to define methods for secure communications among entities, assuring strong authentication, privacy, and anonymity. The ML algorithms used in this framework have been trained and tested using vehicle communications datasets, which have been made publicly available, thus providing easily reproducible and verifiable results. The obtained results show that the proposed Intrusion Detection System (IDS) framework is able to detect attacks accurately, with a low False Positive Rate (FPR). Furthermore, results show that the framework can benefit from using different types of algorithms at different hierarchical levels, selecting light and fast processing algorithms in the lower levels, at the cost of accuracy, and using more precise, accurate, and complex algorithms in nodes higher in the hierarchy.<\/jats:p>","DOI":"10.3390\/info12110455","type":"journal-article","created":{"date-parts":[[2021,11,2]],"date-time":"2021-11-02T12:39:42Z","timestamp":1635856782000},"page":"455","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["An Intelligent Hierarchical Security Framework for VANETs"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5799-7425","authenticated-orcid":false,"given":"F\u00e1bio","family":"Gon\u00e7alves","sequence":"first","affiliation":[{"name":"Algoritmi Center, University of Minho, 4710-057 Braga, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5892-1289","authenticated-orcid":false,"given":"Joaquim","family":"Macedo","sequence":"additional","affiliation":[{"name":"Algoritmi Center, University of Minho, 4710-057 Braga, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1501-2752","authenticated-orcid":false,"given":"Alexandre","family":"Santos","sequence":"additional","affiliation":[{"name":"Algoritmi Center, University of Minho, 4710-057 Braga, Portugal"}]}],"member":"1968","published-online":{"date-parts":[[2021,11,2]]},"reference":[{"key":"ref_1","unstructured":"Cseh, C. (1998, January 21\u201321). Architecture of the dedicated short-range communications (DSRC) protocol. Proceedings of the VTC 98. 48th IEEE Vehicular Technology Conference, Ottawa, ON, Canada."},{"key":"ref_2","unstructured":"IEEE (2010). IEEE Standard for Information Technology\u2014Local and Metropolitan Area Networks\u2014Specific Requirements\u2014Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 6: Wireless Access in Vehicular Environments, IEEE."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"218","DOI":"10.24138\/jcomss.v14i3.550","article-title":"Agnostic and Modular Architecture for the Development of Cooperative ITS Applications","volume":"14","author":"Dias","year":"2018","journal-title":"J. Commun. Softw. Syst."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.comcom.2014.02.020","article-title":"VANET security surveys","volume":"44","author":"Engoulou","year":"2014","journal-title":"Comput. Commun."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.comcom.2014.01.012","article-title":"A survey of intrusion detection in wireless network applications","volume":"42","author":"Mitchell","year":"2014","journal-title":"Comput. Commun."},{"key":"ref_6","unstructured":"Witten, I.H., and Frank, E. (2016). Data Mining: Practical Machine Learning Tools and Techniques, Morgan Kaufmann. Chapter 7."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Aburomman, A.A., and Reaz, M.B.I. (2016, January 14\u201316). Survey of learning methods in intrusion detection systems. Proceedings of the 2016 International Conference on Advances in Electrical, Electronic and Systems Engineering (ICAEES), Putrajaya, Malaysia.","DOI":"10.1109\/ICAEES.2016.7888070"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Goncalves, F., Ribeiro, B., Gama, O., Santos, A., Costa, A., Dias, B., Macedo, J., and Nicolau, M.J. (2019, January 28\u201330). A Systematic Review on Intelligent Intrusion Detection Systems for VANETs. Proceedings of the 2019 11th International Congress on Ultra Modern Telecommunications and Control Systems and Workshops (ICUMT), Dublin, Ireland.","DOI":"10.1109\/ICUMT48472.2019.8970942"},{"key":"ref_9","doi-asserted-by":"crossref","unstructured":"Goncalves, F., Macedo, J., and Santos, A. (2021, January 23\u201325). Evaluation of VANET Datasets in context of an Intrusion Detection System. Proceedings of the 29th International Conference on Software, Telecommunications and Computer Networks (SoftCOM 2021), Split, Croatia.","DOI":"10.23919\/SoftCOM52868.2021.9559058"},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Raya, M., and Hubaux, J.P. (2005, January 2). The security of VANETs. Proceedings of the 2nd ACM international workshop on Vehicular ad hoc networks\u2014VANET\u201905, Cologne, Germany.","DOI":"10.1145\/1080754.1080774"},{"key":"ref_11","first-page":"1","article-title":"A dynamic key distribution protocol for PKI-based VANETs","volume":"1","author":"Hesham","year":"2011","journal-title":"IFIP Wirel. Days"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Bellur, B. (December, January 30). Certificate Assignment Strategies for a PKI-Based Security Architecture in a Vehicular Network. Proceedings of the IEEE GLOBECOM 2008\u20142008 IEEE Global Telecommunications Conference, New Orleans, LA, USA.","DOI":"10.1109\/GLOCOM.2008.ECP.355"},{"key":"ref_13","unstructured":"Liu, Q., Wu, Q., and Yong, L. (2013). A hierarchical security architecture of VANET. Cyberspace Technol., 6\u201310."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Wagan, A.A., Mughal, B.M., Hasbullah, H., and Iskandar, B.S. (2010, January 26\u201328). VANET Security Framework for Trusted Grouping using TPM Hardware. Proceedings of the 2010 Second International Conference on Communication Software and Networks, Singapore.","DOI":"10.1109\/ICCSN.2010.115"},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Bariah, L., Shehada, D., Salahat, E., and Yeun, C.Y. (2015, January 6\u20139). Recent advances in VANET security: A survey. Proceedings of the 2015 IEEE 82nd Vehicular Technology Conference, VTC Fall 2015, Boston, MA, USA.","DOI":"10.1109\/VTCFall.2015.7391111"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"142206","DOI":"10.1109\/ACCESS.2021.3120626","article-title":"Intrusion Detection System Using Machine Learning for Vehicular Ad Hoc Networks Based on ToN-IoT Dataset","volume":"9","author":"Gad","year":"2021","journal-title":"IEEE Access"},{"key":"ref_17","unstructured":"Moustafa, N. (2021, October 05). TON-IOT. Dataset. Available online: https:\/\/research.unsw.edu.au\/projects\/toniot-datasets."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Alsarhan, A., Alauthman, M., Alshdaifat, E., Al-Ghuwairi, A.R., and Al-Dubai, A. (2021). Machine Learning-driven optimization for SVM-based intrusion detection system in vehicular ad hoc networks. J. Ambient. Intell. Humaniz. Comput., 1\u201310.","DOI":"10.1007\/s12652-021-02963-x"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"100013","DOI":"10.1016\/j.array.2019.100013","article-title":"A novel Intrusion Detection System against spoofing attacks in connected Electric Vehicles","volume":"5","author":"Kosmanos","year":"2020","journal-title":"Array"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Song, J., Takakura, H., Okabe, Y., Eto, M., Inoue, D., and Nakao, K. (2011, January 5). Statistical analysis of honeypot data and building of Kyoto 2006+ dataset for NIDS evaluation. Proceedings of the First Workshop on Building Analysis Datasets and Gathering Experience Returns for Security\u2014BADGERS \u201911, Kyoto, Japan.","DOI":"10.1145\/1978672.1978676"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Tavallaee, M., Bagheri, E., Lu, W., and Ghorbani, A.A. (2009, January 8\u201310). A detailed analysis of the KDD CUP 99 data set. Proceedings of the IEEE Symposium on Computational Intelligence for Security and Defense Applications, CISDA 2009, CISDA\u201909, Ottawa, ON, Canada.","DOI":"10.1109\/CISDA.2009.5356528"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"666","DOI":"10.1002\/sec.200","article-title":"A stochastic learning automata-based solution for intrusion detection in vehicular ad hoc networks","volume":"4","author":"Misra","year":"2011","journal-title":"Secur. Commun. Netw."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Tian, D., Wang, Y., Lu, G., and Yu, G. (22010, January 21\u201324). A vehicular ad hoc networks intrusion detection system based on BUSNet. Proceedings of the 2010 2nd International Conference on Future Computer and Communication, ICFCC 2010, Wuhan, China.","DOI":"10.1109\/ICFCC.2010.5497798"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1719","DOI":"10.1587\/transinf.E97.D.1719","article-title":"Data mining intrusion detection in vehicular ad hoc network","volume":"E97-D","author":"Liu","year":"2014","journal-title":"IEICE Trans. Inf. Syst."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.compeleceng.2015.02.018","article-title":"An accurate and efficient collaborative intrusion detection framework to secure vehicular networks","volume":"43","author":"Sedjelmaci","year":"2015","journal-title":"Comput. Electr. Eng."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Ali Alheeti, K.M., and McDonald-Maier, K. (2016, January 7\u20138). Hybrid intrusion detection in connected self-driving vehicles. Proceedings of the 2016 22nd International Conference on Automation and Computing, ICAC 2016: Tackling the New Challenges in Automation and Computing, Colchester, UK.","DOI":"10.1109\/IConAC.2016.7604962"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.eswa.2015.12.006","article-title":"CEAP: SVM-based intelligent detection model for clustered vehicular ad hoc networks","volume":"50","author":"Wahab","year":"2016","journal-title":"Expert Syst. Appl."},{"key":"ref_28","first-page":"23","article-title":"Hybrid fuzzy multi-criteria decision making based multi cluster head dolphin swarm optimized IDS for VANET","volume":"12","author":"Sharma","year":"2018","journal-title":"Veh. Commun."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"74260","DOI":"10.1109\/ACCESS.2018.2883426","article-title":"A Secure and Efficient Certificateless Authentication Scheme With Unsupervised Anomaly Detection in VANETs","volume":"6","author":"Tan","year":"2018","journal-title":"IEEE Access"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1109\/TSIPN.2018.2801622","article-title":"Distributed Privacy-Preserving Collaborative Intrusion Detection Systems for VANETs","volume":"4","author":"Zhang","year":"2018","journal-title":"IEEE Trans. Signal Inf. Process. Over Netw."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Ayoob, A., Su, G., and Al, G. (2018). Hierarchical Growing Neural Gas Network (HGNG)-Based Semicooperative Feature Classifier for IDS in Vehicular Ad Hoc Network (VANET). J. Sens. Actuator Netw., 7.","DOI":"10.3390\/jsan7030041"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Gon\u00e7alves, F., Ribeiro, B., Gama, \u00d3., Santos, J., Costa, A., Dias, B., Nicolau, M.J., Macedo, J., and Santos, A. (2020, January 7\u201311). Synthesizing Datasets with Security Threats for Vehicular Ad-Hoc Networks. Proceedings of the IEEE Globecom 2020: 2020 IEEE Global Communications Conference (GLOBECOM\u20192020), Taipei, Taiwan.","DOI":"10.1109\/GLOBECOM42002.2020.9348149"},{"key":"ref_33","unstructured":"DCAITI (2020, November 12). VSimRTI. Available online: https:\/\/www.dcaiti.tu-berlin.de\/research\/simulation\/."},{"key":"ref_34","unstructured":"ETSI (2014). ETSI EN 302 637-2 V1.3.1 Intelligent Transport Systems (ITS), ETSI. Vehicular Communications; Basic Set of Applications; Part 2: Specification of Cooperative Awareness Basic Service."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Gon\u00e7alves, F., Santos, A., Costa, A., Dias, B., Ribeiro, B., Macedo, J., Nicolau, M.J.N., Sousa, S., Gama, O., and Barros, S. (2017, January 6\u20138). Hybrid Model for Secure Communications and Identity Management in Vehicular Ad Hoc Networks. Proceedings of the 9th International Congress on Ultra Modern Telecommunications and Control Systems (ICUMT\u20192017), Munich, Germany.","DOI":"10.1109\/ICUMT.2017.8255170"},{"key":"ref_36","unstructured":"Ribeiro, B., Gon\u00e7alves, F., Hapanchak, V., Gama, \u00d3., Barros, S., Ara\u00fajo, P., Costa, A., Nicolau, M.J., Dias, B., and Macedo, J. (November, January 28). PlaSA-Platooning Service Architecture. Proceedings of the 8th ACM Symposium on Design and Analysis of Intelligent Vehicular Networks and Applications, Montreal, QC, Canada."},{"key":"ref_37","unstructured":"Gon\u00e7alves, F., Ribeiro, B., Hapanchak, V., Barros, S., Gama, O., Ara\u00fajo, P., Nicolau, M.J., Dias, B., Macedo, J., and Costa, A. (November, January 28). Secure Management of Autonomous Vehicle Platooning. Proceedings of the 14th ACM International Symposium on QoS and Security for Wireless and Mobile Networks, Q2SWinet\u201918, Montreal, QC, Canada."},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Ribeiro, B., Gon\u00e7alves, F., Santos, A., Nicolau, M., Dias, B., Macedo, J., and Costa, A. (2017, January 21\u201323). Simulation and Testing of a Platooning Management Protocol Implementation. Proceedings of the International Conference on Wired\/Wireless Internet Communication, St. Petersburg, Russia.","DOI":"10.1007\/978-3-319-61382-6_14"},{"key":"ref_39","unstructured":"Gon\u00e7alves, F., Santos, A., and Macedo, J. (2021). V2X Security Threats for Cluser-Based Evaluation [Data Set], Zenodo."}],"container-title":["Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2078-2489\/12\/11\/455\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T07:24:52Z","timestamp":1760167492000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2078-2489\/12\/11\/455"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,11,2]]},"references-count":39,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2021,11]]}},"alternative-id":["info12110455"],"URL":"https:\/\/doi.org\/10.3390\/info12110455","relation":{},"ISSN":["2078-2489"],"issn-type":[{"value":"2078-2489","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,11,2]]}}}