Master Thesis - Intelligent Fuzzing and Vulnerability Detection for Automotive Ethernet and Diagnost
Intelligent Fuzzing and Vulnerability Detection for Automotive Ethernet and Diagnostic Protocols
Introduction
Thesis work is an excellent way to get closer to Scania and build relationships for the future. Many of today's employees began their Scania career with their degree project.
Background
Modern vehicle architectures increasingly depend on Ethernet-based communication protocols such as SOME/IP and DoIP, alongside UDS diagnostic services. Malformed packets and unexpected protocol sequences can expose implementation vulnerabilities.
Objective
Design and evaluate a protocol-aware fuzzing framework for automotive communication.
Research objectives
The thesis worker will:
- Design a protocol-aware fuzzing framework for automotive communication.
- Develop mutation strategies for DoIP, SOME/IP, and selected UDS services.
- Investigate stateful fuzzing of diagnostic authentication and session transitions.
- Monitor ECU behavior for crashes, timeouts, unexpected responses, and resource exhaustion.
- Compare protocol-aware fuzzing with conventional random fuzzing.
- Develop an automated fuzzing framework, protocol-specific test harnesses, reproducible findings, and a comparative evaluation of coverage, unique failures, and execution efficiency.
Education/program/focus
Indicate education, program or focus: Software development
Number of students: 1
Start date for the thesis work: 2027-01-11
Estimated time required: <6 months
Contact persons and supervisors
Adela Åberg, Unit Head, adela.aberg@scania.com,
Mostafa Imam, Master Thesis supervisor mostafa.imam@scania.com
Publication date from - to
2026-11-05-2026-11-20
Södertälje, SE, 151 38
