Vehicular Communication (VC) systems can greatly enhance road safety and transportation efficiency. Vehicles are equipped with sensors to sense their surroundings and the internal Controller Area Network (CAN) bus. Hence, vehicles are becoming part of a large-scale network, the so-called Internet of Vehicles (IoV). Deploying such a large-scale VC system cannot materialize unless the VC systems are secure and do not expose their users’ privacy. Vehicles could be compromised or their sensors become faulty, thus disseminating erroneous information across the network. Therefore, participating vehicles should be accountable for their actions. Moreover, user privacy is at stake: vehicles should disseminate spatio-temporal information frequently. Due to openness of the wireless communication, an observer can eavesdrop the communication to infer users’ sensitive information, thus profiling users. The objective is to secure the communication, i.e., prevent malicious or compromised entities from affecting the system operation, and ensure user privacy, i.e., keep users anonymous to any external observer but also for security infrastructure entities and service providers.In this thesis, we focus on the identity and credential management infrastructure for VC systems, taking security, privacy, and efficiency into account. We begin with a detailed investigation and critical survey of the standardization and harmonization efforts. We point out the remaining challenges to be addressed in order to build a Vehicular Public-Key Infrastructure (VPKI). We provide a VPKI design that improves upon existing proposals in terms of security and privacy protection and efficiency. More precisely, our scheme facilitates multi-domain operations in VC systems and enhances user privacy, notably preventing linking of pseudonyms based on timing information and offering increased protection in the presence of honest-but-curious VPKI entities. We further extensively evaluate the performance of the full-blown implementation of our VPKI for a large-scale VC deployment. Our results confirm the efficiency, scalability and robustness of our VPKI. / <p>QC 20160927</p>
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:kth-193030 |
Date | January 2016 |
Creators | Khodaei, Mohammad |
Publisher | KTH, Kommunikationsnät, Stockholm |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Licentiate thesis, comprehensive summary, info:eu-repo/semantics/masterThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
Relation | TRITA-EE, 1653-5146 ; 2016:159 |
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