30 hp - Synthetic attack data generation and intrusion detection system on automotive ethernet

Background:
Scania is one of the world’s leading manufacturer of trucks and buses for heavy transports, as well as industrial and marine engines. Transport services and logistics services make up an increasing part of our business, which guarantees Scania’s customers cost-efficient transport solutions and high availability. Over a million Scania vehicles are in active use, in over 100 countries.

In the Connected Systems department within Scania R&D, we develop new solutions for connected vehicles in our Internet of Things (IoT) platform, as part of Scania’s shift towards sustainable transport system. Advanced data analysis capabilities and cybersecurity are essentials in this development. Scania manufactures and administers an enormous fleet of connected vehicles and therefore has a high responsibility to make all the communication (off-board & on-board) secure by design. The on-board infrastructure of the vehicle is resource restrained but it is also important to detect any intrusion from a foreign actor. 

Target/scope:
The aim of this thesis project is attack and defense on the automotive ethernet, i.e. to investigate the possible attack vectors on the automotive ethernet and generate said attack data on it as well as to build an intrusion detection system to detect any attacks on the automotive ethernet. We may use an existing relevant open dataset for this project or synthetically create attack datasets using Scania’s recorded datasets on automotive ethernet from test vehicles. 

Description of the assignment:
1.    Choose a relevant dataset or build a synthetic dataset 
2.    Explore literature on existing modes of attacks 
3.    Build anomaly detection model for intrusion detection 
4.    Evaluate the model and summarize results 

Education/line/direction:
Assign education, line or direction: masters programmes in Machine Learning, Data Science, Computer Science, Engineering Physics, Engineering Mathematics, Media Technology, or similar

Number of students: 1-2 (pairs is preferred but not a requirement, if so, refer each other in the personal letter)
Start date for the Thesis project: January 2025
Estimated timescale: 20 weeks

Contact person and supervisor:
Kuo-Yun Liang, senior data scientist, 08-553 508 33, kuo-yun.liang@scania.com 
Juan Carlos Andresen, group manager, 08-553 835 16, juan-carlos.andresen@scania.com 

Application:
Your application should contain CV, personal letter and copies of grades

Date of publication:
Until 2024-10-31. Applicants will be assessed on a continuous basis until the position is filled. Do not wait until the last date to apply. 

A background check might be conducted for this position. We are conducting interviews continuously and may close the recruitment earlier than the date specified.     

Thesis Worker