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Thesis Work Vehicle Cybersecurity, Attacker Identification using low level characteristics

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At Volvo Cars, we believe that being curious and truly committed to understanding people is the key to future success. We are people who care about other people, working together to create new technologies and innovations for safe, sustainable and convenient mobility. Want to join us?

 

Background

The in-vehicle network of a modern vehicle consists of more than 100 Electronic Control Units (ECUs) that control different parts of the vehicle such as engine, doors, airbags and infotainment system. These ECUs communicate over multiple sub-networks and gateways using different communication technologies including the Controller Area Network (CAN) bus. In recent years, hackers have demonstrated cyberattacks on vulnerable ECUs, to among other things, endanger the safety of passengers. A cyber resilient vehicle must be able to detect an attack on the in-vehicle network and identify the origin of the attack (i.e. determine which ECU mounted the attack) to isolate or patch the vulnerable ECU. However, given that CAN messages are broadcast and do not carry information about the transmitters, the existing intrusion detection systems are incapable of identifying the attacker ECU.

 

Challenge

The focus of this thesis will be on implementing a fingerprinting technique that is based on the low-level characteristics of in-vehicle ECUs (e.g. Clock offset and clock skew). The students are expected to implement an experimental fingerprinting method on a CAN bus prototype and a test vehicle.

We are looking for students who are interested in computer and network security and have knowledge in embedded security or intrusion detection systems.
 

This thesis should answer the following key questions:

a) Which low-level characteristics of ECUs can be used for fingerprinting?

b) How to profile (fingerprint) ECUs based on the identified low-level characteristic?

c) What are the HW/SW requirements of implementing such an approach on real automotive ECUs?

d) How accurate is the implemented fingerprinting technique?

e) How practical and efficient is the proposed fingerprinting technique and what are the deployment challenges?
 

The work in this thesis will be carried out as a collaboration between Volvo Cars and D&IT at Chalmers. After a successful thesis project, students will gain experience in the field of automotive cybersecurity and intrusion detection systems. This thesis work requires interaction with a team of engineers from Volvo Cars which will provide the students an opportunity to gain insight into how research is conducted in the automotive industry.

 

Profile

• One or two MSc. student(s) in their final year with background in Computer Science or similar areas

• Knowledge in cybersecurity, and preferably in intrusion detection systems

• English language fluency, written and spoken

 

Application
We want your application at the latest 2019-11-15

Use the electronic application form at https://group.volvocars.com/careers/students

 

Contact details

Tomas Olovsson, Dept. of Computer Science and Engineering  tomas.olovsson@chalmers.se

Nasser Nowdehi, Volvo Cars nasser.nowdehi@volvocars.com

 

 

Who are we?

Everything we do starts with people. Our purpose is to provide freedom to move, in a personal, sustainable and safe way. We are committed to simplifying our customers’ lives by offering better technology solutions that improve their impact on the world and bringing the most advanced mobility innovations to protect them, their loved ones and the people around them. 


Volvo Cars’ continued success is the result of a collaborative, diverse, and inclusive working environment. The people of Volvo Cars are committed to making a difference in our world. Today, we are one of the most well-known and respected car brands, with over 40,000 employees across the globe. We believe in bringing out the best in each other and harnessing the true power of people. At Volvo Cars your career is designed around your talents and aspirations so you can reach your full potential. Join us on a journey of a lifetime as we create safety, autonomous driving and electrification technologies of tomorrow.

Gothenburg, O, SE

Job requisition ID:  27240

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