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Thesis Work Vehicle Cybersecurity - GNSS Spoofing

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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?

 

GNSS Spoofing/Jamming Attack Detection

 

GNSS is a core component of modern Advanced Driver-Assistance Systems (ADAS) and autonomous navigation systems. However, all GNSS systems in civil and military applications are vulnerable to GNSS spoofing and jamming attacks. For instance, an adversary may launch a GNSS spoofing attack on a vehicle that is in autopilot mode, to cause the vehicle to maneuver off its original route and head toward the spoofed location. The potential safety impact of such attacks on vehicles can be quite devastating. Therefore, a cyber resilient vehicle must be able to detect and mitigate GNSS spoofing and jamming attacks.

 

Challenge

The aim of this thesis is to implement a software-based solution for GNSS spoofing/Jamming attack detection which detects anomalies in the GPS coordinates of the vehicle. The students are expected to perform a literature review on the state-of-the-art GNSS attack detection methods, as well as implementing and evaluating their solution on a realistic automotive environment.

We are looking for students who are interested in computer and network security and have knowledge in embedded security, wireless communication, control systems or anomaly detection systems.

This Master thesis should answer the following key questions:

a) What are the automotive requirements for a GNSS spoofing/jamming attack detection solution?

b) What GNSS attack detection methods are proposed in the literature?

c) Is it possible to use redundant data sources for verifying the reference time and location obtained from the GPS signal? What are the challenges?

d) Which of these methods fulfill the identified automotive requirements and are applicable for automotive environments?

e) How accurate is the implemented detection technique?

f) How practical and efficient is the proposed detection 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 anomaly 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.

 

 

Background & Requirements

 

One or two MSc.students(s) in their final year with background in Computer Science or similiar areas.

Knowledge in cybersecurity, wireless communication or control systems

English language fluency, written and spoken

 

Contact

 

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

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

 

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

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

 

 

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:  27373

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