Resilient in-network aggregation for vehicular networks

Applications for vehicular ad hoc networks (VANETs) are an active field of research with the potential to significantly contribute to driver safety, traffic efficiency, and comfort. Messages are typically exchanged and forwarded between vehicles using wireless communication, thereby creating a wireless ad hoc network. Especially traffic efficiency applications require the dissemination of information over long distances. Two of the most prevalent challenges in designing suitable ad hoc communication protocols are dealing with the limited wireless channel capacity, as well as ensuring the resilience of communication protocols against potential attackers.\ud \ud The focus of this thesis is on the resilience of in-network information aggregation mechanisms for VANETs. In aggregation mechanisms, vehicles collaboratively exchange information and summarize this information as it is disseminated within the network. In contrast to traditional protocols, which often aggregate information at a centralized entity, the aggregation close to the information sources saves bandwidth and provides scalability. Yet, malicious users may be able to inject false information or even alter information summaries to disturb normal system operation. Both types of attacks are hard to detect, because original observations are usually discarded after aggregation and are not available to verify the correctness of claimed aggregated information. By addressing resilient in-network aggregation, this thesis provides solutions that contribute to both channel capacity conservation and protocol resilience.\ud \ud Evaluation results of individual proposed mechanisms indicate an inherent trade-off between bandwidth conservation and resilience against attackers. Therefore, a generic mechanism combination and adaptation framework is proposed, which uses each mechanism in the situations for which it is most suitable, avoiding drawbacks of individual mechanisms in other traffic situations. The combination and adaptation framework, thereby, demonstrates that bandwidth- efficient and scalable information dissemination using in-network aggregation is feasible while maintaining resilience against a broad range of possible attacks