In this dissertation, we study an important problem of security in wireless networks. We study different attacks and defense strategies in general and more specifically jamming attacks. We begin the dissertation by providing a tutorial introducing the operations research community to the various types of attacks and defense strategies in wireless networks. In this tutorial, we give examples of mathematical programming models to model jamming attacks and defense against jamming attacks in wireless networks. Later we provide a comprehensive taxonomic classification of the various types of jamming attacks and defense against jamming attacks. The classification scheme will provide a one stop location for future researchers on various jamming attack and defense strategies studied in literature. This classification scheme also highlights the areas of research in jamming attack and defense against jamming attacks which have received less attention and could be a good area of focus for future research. In the next chapter, we provide a bi-level mathematical programming model to study jamming attack and defense strategy. We solve this using a game-theoretic approach and also study the impact of power level, location of jamming device, and the number of transmission channels available to transmit data on the attack and defense against jamming attacks. We show that by increasing the number of jamming devices the throughput of the network drops by at least 7%. Finally we study a special type of jamming attack, flow-jamming attack. We provide a mathematical programming model to solve the location of jamming devices to increase the impact of flow-jamming attacks on wireless networks. We provide a Benders decomposition algorithm along with some acceleration techniques to solve large problem instances in reasonable amount of time. We draw some insights about the impact of power, location and size of the network on the impact of flow-jamming attacks in wireless networks.

Cybersecurity has become an increasingly important concern for both military and civilian infrastructure globally. Because of the complexity that comes with wireless networks, adversaries have many means of infiltration and disruption of wireless networks. While there is much research done in defending these networks, understanding the robustness of these networks is tantamount for both designing new networks and examining possible security deficiencies in preexisting networks. This dissertation proposes to examine the robustness of wireless networks on three major fronts: the physical layer, the data-link layer, and the network layer. At the physical layer, denial-of-service jamming attacks are considered, and both additive interference and no interference are modeled in an optimal configuration and five common network topologies. At the data-link layer, data transmission efficacy and denial-of-sleep attacks are considered with the goal of maximizing throughput under a constrained lifetime. At the network layer, valid and anomalous communications are considered with the goal of classifying those anomalous communications apart from valid ones. This dissertation proposes that a thorough analysis of the aforementioned three layers provides valuable insights to robustness on general wireless networks.

Connected and autonomous vehicles are emerging technologies that have fostered the Intelligent Transportation System (ITS). ITS has the objective of optimizing traffic safety, mobility, and fuel consumption. To achieve this, a range of different services are provided that utilize communication in a vehicular network. One of these services that has received a lot of attention lately due to its ongoing standardization is the Maneuver Coordination Service (MCS). MCS has already shown great potential in the support of complex traffic areas, also called Transition Area (TA), where vehicles must cooperate to avoid Transition of Controls (ToCs). ITS-services often rely on communicated data; small errors, such as inaccessible or incorrect data, can cause the system to behave incorrectly. Signal interference (jamming) can cause communication interruptions, making vehicles unaware of each other. Incorrect data can be intentional due to data injection attacks, but also unintentional due to malfunctioning sensors, making vehicles incorrectly aware of each other. Incorrect behavior in systems such as ITS can lead to traffic congestion or even life-threatening collisions. This study focuses on MCS and examines traffic behavior when the service, in a generic traffic scenario, is subjected to jamming and falsification attacks with a variety of strategies (negative and positive speed, acceleration and position offset). We considered external attackers (not authenticated) that can disrupt communication, as well as internal attackers (authenticated) that are limited to tampering with outgoing data. Through severe collisions and travel time delays, the results show an impact on both safety and mobility. The results also show that different attacks with different impacts on the adversary can cause similar effects on the traffic, thus allowing the adversary to choose attacks based on the desired impact and its rationality, i.e. its willingness to be part of the impact. The study also proposes an extension to an already proposed Maneuver Coordination Protocol (MCP). We show that our extended MCP can be beneficial in avoiding dangerous maneuvers that could lead to collisions with cars in the blind spot. / Uppkopplade och autonoma fordon är framväxande teknologier som har främjat Intelligenta Transporteringssystem (ITS). ITS har som mål att optimera trafiksäkerhet, mobilitet och bränsleförbrukning. För att uppnå detta tillhandahålls en rad olika tjänster som utnyttjar kommunikation i ett fordonsnät. En av dessa tjänster som har fått mycket uppmärksamhet under den senaste tiden, tack vare sin pågående standardisering, är Manöverkoordinationtjänsten (MCS). MCS har redan visat stor potential för att stödja komplexa trafikområden, även kallade Övergångsområden (TA), där fordon måste samarbeta för att undvika kontrollövergångar (ToCs). ITS-tjänster förlitar sig ofta på kommunicerad data; små fel, som otillgängliga eller felaktiga data, kan göra att systemet beter sig felaktigt. Signalstörningar kan orsaka kommunikationsavbrott, vilket gör fordon omedvetna om varandra. Felaktig data kan vara avsiktliga på grund av datainjektionsattacker, men också oavsiktliga på grund av felaktiga sensorer, vilket gör fordon felaktigt medvetna om varandra. Felaktigt beteende i system som ITS kan leda till trafikstockningar eller till och med livshotande kollisioner. Denna studie fokuserar på MCS och undersöker trafikbeteendet när tjänsten, i ett generiskt trafikscenario, utsätts för signalstörningar och förfalskningsattacker med en mängd olika strategier (negativ och positiv hastighet, acceleration och positionsförskjutning). Vi tog hänsyn till externa angripare (ej autentiserade) som kan störa kommunikationen, såväl som interna angripare (autentiserade) som är begränsade till att manipulera utgående data. Genom allvarliga kollisioner och restidsförseningar visar resultaten en inverkan på både säkerhet och mobilitet. Resultaten visar också att olika attacker med olika inverkan på angriparen kan orsaka liknande effekter på trafiken, vilket gör att angriparen kan välja attacker baserat på den önskade effekten och rationaliteten, d.v.s. dens villighet att vara en del av påverkan. Studien föreslår också en utökning av en redan föreslagen MCP. Vi visar att vårt utökade MCP kan vara till nytta för att undvika farliga manövrar som kan leda till kollisioner med bilar i döda vinkeln.