The Key to Intelligent Transportation Systems: Identity and Credential Management for Secure and Privacy-Preserving Vehicular Communication Systems
Sammanfattning: Vehicular Communication (VC) systems can greatly enhance road safety and transportation efficiency and enable a variety of applications providing traffic efficiency, environmental hazards, road conditions and infotainment. Vehicles are equipped with sensors and radars to sense their surroundings and external environment, as well as with an 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. On the one hand, vehicles could be compromised or their sensors become faulty, thus disseminating erroneous information across the network. Therefore, participating vehicles should be held accountable for their actions and credentials (their Long Term Certificates (LTCs) and their pseudonyms) can be efficiently revoked and disseminated in a timely manner throughout a large-scale (multi-domain) VC system. On the other hand, user privacy is at stake: according to standards, vehicles should disseminate spatio-temporal information frequently, e.g., location and velocity. Due to the openness of the wireless communication, an observer can eavesdrop the vehicular communication to infer users’ sensitive information, and possibly profile users based on different attributes, e.g., trace their commutes and identify home/work locations. 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. This is not very straightforward because accountability and privacy, at the same time, appear contradictory. In this thesis, we first 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, along with industrial projects and proposals. We point out the remaining challenges to be addressed in order to build a central building block of secure and privacy-preserving VC systems, a Vehicular Public-Key Infrastructure (VPKI). Towards that, we provide a secure and privacy-preserving 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, i.e., scalability, efficiency, and robustness, of the full-blown implementation of our VPKI for a large-scale VC deployment. We provide tangible evidence that it is possible to support a large area of vehicles by investing in modest computing resources for the VPKI entities. Our results confirm the efficiency, scalability and robustness of our VPKI.As a second main contribution of this thesis, we focus on the distribution of Certificate Revocation Lists (CRLs) in VC systems. The main challenges here lie exactly in (i) crafting an efficient and timely distribution of CRLs for numerous anonymous credentials, pseudonyms, (ii) maintaining strong privacy for vehicles prior to revocation events, even with honest-but-curious system entities, (iii) and catering to computation and communication constraints of on-board units with intermittent connectivity to the infrastructure. Relying on peers to distribute the CRLs is a double-edged sword: abusive peers could "pollute" the process, thus degrading the timely CRLs distribution. We propose a vehicle-centric solution that addresses all these challenges and thus closes a gap in the literature. Our scheme radically reduces CRL distribution overhead: each vehicle receives CRLs corresponding only to its region of operation and its actual trip duration. Moreover, a "fingerprint" of CRL ‘pieces’ is attached to a subset of (verifiable) pseudonyms for fast CRL ‘piece’ validation (while mitigating resource depletion attacks abusing the CRL distribution). Our experimental evaluation shows that our scheme is efficient, scalable, dependable, and practical: with no more than 25 KB/s of traffic load, the latest CRL can be delivered to 95% of the vehicles in a region (15x15 KM) within 15s, i.e., more than 40 times faster than the state-of-the-art. Overall, our scheme is a comprehensive solution that complements standards and can catalyze the deployment of secure and privacy-protecting VC systems. As the third main contribution of the thesis, we focus on enhancing location privacy protection: vehicular communications disclose rich information about the vehicles and their whereabouts. Pseudonymous authentication secures communication while enhancing user privacy. To enhance location privacy, cryptographic mix-zones were proposed to facilitate vehicles covertly transition to new ephemeral credentials. The resilience to (syntactic and semantic) pseudonym linking (attacks) highly depends on the geometry of the mix-zones, mobility patterns, vehicle density, and arrival rates. Our experimental results show that an eavesdropper could successfully link 73% of pseudonyms (during non-rush hours) and 62% of pseudonyms (during rush hours) after vehicles change their pseudonyms in a mix-zone. To mitigate such inference attacks, we present a novel cooperative mix-zone scheme that enhances user privacy regardless of the vehicle mobility patterns, vehicle density, and arrival rate to the mix-zone. A subset of vehicles, termed relaying vehicles, are selected to be responsible for emulating non-existing vehicles. Such vehicles cooperatively disseminate decoy traffic without affecting safety-critical operations: with 50% of vehicles as relaying vehicles, the probability of linking pseudonyms (for the entire interval) drops from 68% to 18%. On average, this imposes 28 ms extra computation overhead, per second, on the Roadside Units (RSUs) and 4.67 ms extra computation overhead, per second, on the (relaying) vehicle side; it also introduces 1.46 KB/sec extra communication overhead by (relaying) vehicles and 45 KB/sec by RSUs for the dissemination of decoy traffic. Thus, user privacy is enhanced at the cost of low computation and communication overhead.
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