Thesis Topics

The alps see a surge of trail parks being built. These trails include frequent turns and jumps which are often ridden at high speeds. If bikes block the trail due to a stop or accident, limited line-of-sight can lead to collisions and severe accidents when following bikes crash into the blocking bike. With this work, we want to investigate if V2X communication can provide blocked trail warnings to approaching bikes so that riders can reduce their speed and avoid accidents. For this, a number of technologies that have been developed for collision warning in automotive and street-based scenarios need to be investigated, adapted, and tested for suitability. This includes the V2X communication module and antenna, that need to be adjusted to fit into a bike. Communication ranges and reliability have to be tested in realistic outdoor settings. Second, it needs to be reliably determined whether a bike actually blocks a trail or whether the rider just stopped next to it. For this purpose, GPS accuracy alone is insufficient and might have to coupled with crash detection using motion sensors or camera-based image recognition to detect whether a bike blocks a trail or not. Last but not least, a suitable user interface has to be developed and tested that allows to warn approaching drivers in a reliable and intuitive way which works even during trail rides. The envisioned thesis or project can address one or multiple of these challenges, multiple students could also collaborate on the topic. The project is collaboration between Ulm University and University of Trento. After prototype development, field tests in the Alps in South Tyrolia / Alto Adige are planned.

In the future, vehicles will be able to exchange information with each other and with infrastructure. In this way, safety-cirtical applications such as Cooperative Intersection Management (CIM) can be realized that use data sent by other entities such as vehicles or infrastructure. Since these applications are safety-critical, it is important for the application to evaluate the trustworthiness of the data provided by other entities before using them in these applications. How trustworthy the data is can be specified by the sender of the message. The structure of the messages sent by the entities is specified by ETSI (European Telecommunications Standards Institute). In the current standard of the messages, such trust opinions indicating the trustworhtiness of the data are not defined. Therefore, in this thesis/project ETSI messages such as CAMs are extened so that trust opinions can be set for the provided data. In the second step, these defined messages are implemented in a traffic and network simulation tool. Finally, the impact of the extended ETSI messages is compared to the standard ETSI messages based on certain performance metrics.

In the context of Cooperative, connected and automated mobility, a vehicle relies on data from multiple sources to drive autonomously. On the one hand, it relies on data provided by an external entity, such as a road side unit or another vehicle, which is received over the V2X network. On the other hand, it relies on data provided by internal entities within the vehicle, such as a sensor installed in the vehicle or an ECU in the vehicle. Since the autonomous driving functionality is very safety critical, it is important for the function to evaluate the trustworthiness of the data provided by the internal and external entities. In this project/thesis, several entities in the context of an autonomous vehicle are selected. Examples of internal entities could be a GNSS sensor or a camera. Examples of external entities could be another vehicle or a road side unit. Based on the selected entities, trust sources are determined to provide evidence of whether the entity is trustworhty or not. Such trust sources could be security controls such as an IDS or Secure Boot. Finally, an approach is created that determines a trust opinion about the selected entitiy based on the selected trust sources in the context of subjective logic. This calcualated trust opinion describes the trustworthiness of this entity.

In the future, vehicles will exchange information regarding the current traffic situation and planned maneuvers. While this has the potential to improve safety and fuel efficiency though cooperative driving, it opens up a novel attack vector: malicious actors might inject incorrect information, which could lead to accidents and thus poses a serious threat to safety. One approach to mitigate such attacks makes use of Subjective Trust Networks: vehicles form Trust Opinions on other vehicles, which are expressed using Subjective Logic and stored in a graph structure. Different vehicles can merge their Trust Networks in order to gain a more complete picture of the trustworthiness of their communication partners and make more informed decisions. However, privacy and safety considerations forbid that different vehicles simply exchange their trust networks. This thesis/project should investigate the feasibility of merging an evaluating Subjective Trust Networks using Secure Multiparty Computation (SMPC). For this, it is first necessary to precisely define the task at hand: Which calculations must be performed under SMPC in order to protect confidential information? Which information cannot be protected? Second, a prototype for an example scenario in which vehicles merge and evaluate their trust Networks should be implemented using a suitable framework for SMPC. Third, benchmarks should be performed that show the (non-)applicability of SMPC for the described use-case.

Abstract: Policy Languages such as XACML or ALFA are well-known and well-defined in the area of access control. With Zero Trust Service Function Chaining (ZTSFC) [https://journal.ub.tu-berlin.de/eceasst/article/view/1138], an advanced Zero Trust (ZT) architecture, new requirements came up for such Policy Languages. The goal of the thesis is to set up a list of this requirements, to identify missing features in existing policy languages. Based on this, the most promising policy language is to be extended by this missing features.

Cooperative Intersection Management Systems are a promising approach to improve efficiency and safety at intersections. For this purpose, communicating vehicles are needed that can communicate with each other and with infrastructure, which is also referred to as V2X-Communication. Based on the information exchanged between the vehicles and the infrastructure, a Cooperative Intersection Management System can be realized. There exist various approaches to realized such a Cooperative Intersection Management System. Therefore, the first step of the thesis/project is to conduct a survey on existing approaches of a Cooperative Intersection Management System. Based on this survey, the most promising approach will be selected. In the next step, the selected approach will be implemented in a traffic simulation environment called CARLA. Finally, a performance analysis of the implemented approach will be conducted and compared to a state-of-the-art traffic light system.

An autonomous vehicle is equipped with a variety of sensors that produce large quantites of data which the vehicle uses to run a lot of different safety-critical functions, such as Cooperative Adaptive Cruise Control or Park Assist. In this thesis, we focus on the trust between the vehicle computer and other in-vehicle components that it relies upon to provide non-compromised data as input to different safety-critical functions. The goal of the thesis is to build a tool that will automate building of in-vehicular trust models based on a system model of a vehicle. A system model of a simplified vehicle will first need to be built by using the System Modeling Language (SysML). This model will serve as an input to the automation tool that needs to output a trust model in form of a Subjective Trust Network. The methodology for building such trust models within the framework of Subjective Logic will be provided.

Service Function Chaining (SFC) is a technice to steer traffic through specific network services. To proof that the traffic was actually forwarded through the specified services, a Proof Of Transit (PoT) is used. In this project, different PoT approaches are compared and the most promising solution implemented in a HTTPS-based SFC environment.

Security assessments of networked systems require knowledge about the utilized communication protocol. For proprietary protocols without known specification and with only limited access to the end-points, the only source of information is the communication itself. To correctly conclude from the captured byte stream to message-formats, -types, and finally a protocol model, structure, message- and field-boundaries, data-type, and semantics need to be inferred. After an initial inference procedure, it is desirable to refine the existing protocol model. Actively probing an entity for the validity of message syntaxes allows to targetedly enhance the knowledge about the protocol. To do this efficiently a smart method of automatically generating test-cases depending on the current protocol model needs to be developed.