MSc Thesis - Forensically sound logging for connected vehicles
Göteborg, SE, 417 15
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Background of thesis work
Safety is a major concern in the transportation sector, and cybersecurity is a vital prerequisite to ensure it, especially in the age of connected vehicles. As vehicles become increasingly interconnected with backend services and external infrastructure, the likelihood and potential impact of cybersecurity incidents increase. When such incidents occur, reliable forensic evidence is needed to understand what happened, determine the origin and sequence of events, and support further investigation.
Vehicle and backend logs can provide important forensic evidence. However, conventional logging mechanisms do not necessarily guarantee that the collected information is authentic, complete, traceable, or protected against manipulation. Evidence may pass through several components and communication links before reaching a backend system. During this process, an attacker may attempt to modify, delete, insert, replay, or reorder log records. Intermittent connectivity, clock differences, component failures, and limited vehicle resources introduce additional challenges.
Forensically sound logging therefore requires mechanisms that preserve properties such as integrity, authenticity, provenance, event ordering, freshness, and chain of custody. The protocol should also consider confidentiality, privacy, availability, communication overhead, and the constraints of embedded vehicle systems. Approaches from automotive cybersecurity, digital forensics, distributed systems, cloud infrastructure, and embedded systems address parts of this problem, but further research is needed to determine how they can be combined into a protocol suitable for connected vehicles.
For this thesis, the focus is on designing an OEM- and hardware-agnostic logging protocol for the secure collection and preservation of forensic evidence from connected vehicles to backend systems. The work will investigate which forensic and security properties the protocol should provide, how provenance and chain of custody can be represented, and how selected properties can be formally specified and verified. A proof-of-concept demonstrator will be developed and evaluated against representative threats, failure scenarios, and performance requirements.
We are now looking for students who are ready to accept challenging tasks within this exciting area.
Do you want to be part of the team ensuring the cybersecurity of next-generation commercial vehicles?
Background of students
Candidates should be in the final year of their master’s studies. Suitable masters’ programmes include Software Engineering, Computer Science, Cybersecurity, and IT. Candidates with equivalent background from other programmes will also be considered. To be considered, it is very important that the students have taken relevant courses in cybersecurity, and it is highly recommended to point out any cybersecurity experience in the resume. Other relevant courses include AI/ML, distributed systems, logic, and similar courses.
General programming knowledge is also considered an important skill due to the need to develop the proof-of-concept. As the work environment is highly international, good skills in English, both oral and written, are required.
Description of thesis work
The thesis work will be carried out at the Volvo Trucks Technology & Industrial Division campus in Lundby, Gothenburg. Workwise, the thesis will be a mix of theoretical and practical programming tasks, as outlined below.
- Systematic study of the state of the art in forensics, logging, and provenance protocols.
- Creation of a proposal of a forensically sound logging protocol with provenance abilities.
- Proof of concept design and development & evaluation of implementation
After a successful thesis project, students will gain experience in the field of automotive E/E system development, and security design. Students will also have an opportunity to gain insights into how research is conducted in the automotive industry.
Last Date of application - 18th October 2026
Thesis level: Master
Language: English
Starting date: January 2027
Number of Students: The thesis is suitable for two students working in collaboration. Please state the name of a preferred thesis partner in the application to make it easier to pair people together and assess a joint application.
Industrial tutors: Volvo Trucks Technology & Industrial Division
Torbjörn Livén, torbjorn.liven@volvo.com
Christian Sandberg, christian.sandberg@volvo.com
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