Author ORCID Identifier

Year of Publication


Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation




Computer Science

First Advisor

Dr. D. Manivannan

Second Advisor

Dr. Sherali Zeadally


Given the enormous interest in self-driving cars, Vehicular Ad hoc NETworks (VANETs) are likely to be widely deployed in the near future. Cloud computing is also gaining widespread deployment. Marriage between cloud computing and VANETs would help solve many of the needs of drivers, law enforcement agencies, traffic management, etc. The contributions of this dissertation are summarized as follows: A Secure and Distributed Architecture for Vehicular Cloud: Ensuring security and privacy is an important issue in the vehicular cloud; if information exchanged between entities is modified by a malicious vehicle, serious consequences such as traffic congestion and accidents can occur. In addition, sensitive data could be lost, and human lives also could be in danger. Hence, messages sent by vehicles must be authenticated and securely delivered to vehicles in the appropriate regions. In this dissertation, we present a secure and distributed architecture for the vehicular cloud which uses the capabilities of vehicles to provide various services such as parking management, accident alert, traffic updates, cooperative driving, etc. Our architecture ensures the privacy of vehicles and supports secure message dissemination using the vehicular infrastructure. A Low-Overhead Message Authentication and Secure Message Dissemination Scheme for VANETs: Efficient, authenticated message dissemination in VANETs are important for the timely delivery of authentic messages to vehicles in appropriate regions in the VANET. Many of the approaches proposed in the literature use Road Side Units (RSUs) to collect events (such as accidents, weather conditions, etc.) observed by vehicles in its region, authenticate them, and disseminate them to vehicles in appropriate regions. However, as the number of messages received by RSUs increases in the network, the computation and communication overhead for RSUs related to message authentication and dissemination also increases. We address this issue and present a low-overhead message authentication and dissemination scheme in this dissertation. On-Board Hardware Implementation in VANET: Design and Experimental Evaluation: Information collected by On Board Units (OBUs) located in vehicles can help in avoiding congestion, provide useful information to drivers, etc. However, not all drivers on the roads can benefit from OBU implementation because OBU is currently not available in all car models. Therefore, in this dissertation, we designed and built a hardware implementation for OBU that allows the dissemination of messages in VANET. This OBU implementation is simple, efficient, and low-cost. In addition, we present an On-Board hardware implementation of Ad hoc On-Demand Distance Vector (AODV) routing protocol for VANETs. Privacy-preserving approach for collection and dissemination of messages in VANETs: Several existing schemes need to consider safety message collection in areas where the density of vehicles is low and roadside infrastructure is sparse. These areas could also have hazardous road conditions and may have poor connectivity. In this dissertation, we present an improved method for securely collecting and disseminating safety messages in such areas which preserves the privacy of vehicles. We propose installing fixed OBUs along the roadside of dangerous roads (i.e., roads that are likely to have more ice, accidents, etc., but have a low density of vehicles and roadside infrastructure) to help collect data about the surrounding environment. This would help vehicles to be notified about the events on such roads (such as ice, accidents, etc.).Furthermore, to enhance the privacy of vehicles, our scheme allows vehicles to change their pseudo IDs in all traffic conditions. Therefore, regardless of whether the number of vehicles is low in the RSU or Group Leader GL region, it would be hard for an attacker to know the actual number of vehicles in the RSU/GL region.

Digital Object Identifier (DOI)