Ansaf I. Alrabady

TL;DR: This paper proposes an uncertainty-aware path cloaking algorithm that hides location samples in a dataset to provide a time-to-confusion guarantee for all vehicles and shows that this approach effectively guarantees worst case tracking bounds, while achieving significant data accuracy improvements.

TL;DR: This architecture separates data from identities by splitting communication from data analysis, and promises significant reductions in infrastructure cost because the system can exploit the sensing, computing, and communications devices already installed in many modern vehicles.

TL;DR: A novel time-to-confusion criterion is derived to characterize privacy in a locational data set and a disclosure control algorithm is proposed (called uncertainty-aware path cloaking algorithm) that selectively reveals GPS samples to limit the maximum time- To-Confusion for all vehicles.

TL;DR: In this paper, an on-board diagnosis and prognosis module is used to monitor one or more vehicle buses to identify trouble codes and other information indicating a vehicle problem, and then a remote repair center may receive the message and may identify a software upgrade patch associated with the problem that can be transmitted to the vehicle to upgrade its software to correct the problem.

TL;DR: A control module reflash system includes a control module located in a vehicle that controls at least one function of the vehicle according to stored vehicle software in the control module as discussed by the authors, where the external interface module retrieves a comparison software file from the source external to the vehicle corresponding to the part number and compares the software file and the comparison file.