Please use this identifier to cite or link to this item: https://hdl.handle.net/1822/76479

TitleAn intelligent hierarchical security framework for VANETs
Author(s)Gonçalves, Fábio Raul Costa
Macedo, Joaquim
Santos, Alexandre
KeywordsVANETs
Security
Intrusion detection systems
Machine learning
Issue date2-Nov-2021
PublisherMultidisciplinary Digital Publishing Institute (MDPI)
JournalInformation
CitationGonçalves, F.; Macedo, J.; Santos, A. An Intelligent Hierarchical Security Framework for VANETs. Information 2021, 12, 455. https://doi.org/10.3390/info12110455
Abstract(s)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’ 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.
TypeArticle
URIhttps://hdl.handle.net/1822/76479
DOI10.3390/info12110455
ISSN2078-2489
Publisher versionhttps://www.mdpi.com/2078-2489/12/11/455
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CAlg - Artigos em revistas internacionais / Papers in international journals

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