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The goal of this research was to examine the potential predictive ability of socioeconomic and demographic data for drivers on Kentucky crash occurrence. Identifying unique background characteristics of at-fault drivers that contribute to crash rates and crash severity may lead to improved and more specific interventions to reduce the negative impacts of motor vehicle crashes. The driver-residence zip code was used as a spatial unit to connect five years of Kentucky crash data with socioeconomic factors from the U.S. Census, such as income, employment, education, age, and others, along with terrain and vehicle age. At-fault driver crash counts, normalized over the driving population, were used as the dependent variable in a multivariate linear regression to model socioeconomic variables and their relationship with motor vehicle crashes. The final model consisted of nine socioeconomic and demographic variables and resulted in a R-square of 0.279, which indicates linear correlation but a lack of strong predicting power. The model resulted in both positive and negative correlations of socioeconomic variables with crash rates. Positive associations were found with the terrain index (a composite measure of road curviness), travel time, high school graduation and vehicle age. Negative associations were found with younger drivers, unemployment, college education, and terrain difference, which considers the terrain index at the driver residence and crash location. Further research seems to be warranted to fully understand the role that socioeconomic and demographic characteristics play in driving behavior and crash risk.

Aujourd'hui, nous utilisons de plus en plus d'appareils "connectés" (téléphone portable, badge d'accès ou de transport, carte bancaire NFC, ...), et cette tendance ne va pas s'inverser. Ces appareils requièrent l'utilisation de primitives cryptographiques, embarquées dans des composants électroniques, dans le but de protéger les communications. Cependant, des techniques d'attaques permettent d'extraire de l'information du composant électronique ou fauter délibérément son fonctionnement. Un nouveau médium d'attaque, exploitant les ondes électromagnétiques est en pleine expansion. Ce médium, par rapport à des techniques de fautes à base de perturbations par faisceau LASER, propose l'avantage d’être à relativement faible coût. Nous présentons dans cette thèse la résistance d'un type de bloc cryptographique, à savoir les générateurs de nombres réellement aléatoires, aux ondes électromagnétiques. Nous montrons qu'il est possible d'extraire de l'information sensible du champ électromagnétique produit par le composant électronique, et qu'il est également possible de perturber un générateur en le soumettant à un fort champ électromagnétique harmonique / Nowadays, our society is using more and more connected devices (cellphones, transport or access card NFC debit card, etc.), and this trend is not going to reverse. These devices require the use of cryptographic primitives, embedded in electronic circuits, in order to protect communications. However, some attacks can allow an attacker to extract information from the electronic circuit or to modify its behavior. A new channel of attack, using electromagnetic waves is skyrocketing. This channel, compared to attacks based on LASER beam, is relatively inexpensive. We will, in this thesis, present a new attack, using electromagnetic waves, of a certain type of cryptographic primitive: the true random number generator. We will show that it is possible to extract sensitive information from the electromagnetic radiation coming from the electronic device. We will also show that it is possible to completly modify the behavior of the true random number generator using a strong electromagnetic field