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Master's thesis: Interpretable CAN Bus Intrusion Forensics via Tensor Networks

Teknik, data och digitalt · Mjukvaru- och webbutveckling · Mjukvaruutveckling · Datavetenskap · Cybersäkerhet

I korthet

Denna masteruppsats undersöker användningen av kvant-inspirerade tensor-nätverk för tolkningsbar intrångsdetektering och forensisk analys av CAN-bussar. Målet är att utveckla ett ramverk för anomalidetektering som lär sig normala fordonkommunikationsmönster och identifierar avvikelser associerade med cyberattacker, med en central betoning på jämförbar prestanda med state-of-the-art metoder och överlägsen tolkningsbarhet, reproducerbarhet och forensiskt värde.

Ansvarsområden

  • Conduct a literature review on automotive cybersecurity, CAN bus security, intrusion detection systems, tensor networks, and quantum-inspired machine learning.
  • Study common CAN attack scenarios, including DoS, spoofing, fuzzing, replay, and masquerading attacks.
  • Design suitable feature representations for CAN traffic, incorporating arbitration IDs, payload content, message sequences, and timing information.
  • Develop and implement a tensor network based anomaly detection framework.
  • Investigate interpretability for attributing anomalies to specific CAN messages and communication patterns.
  • Evaluate the proposed method using public automotive cybersecurity datasets and compare results with conventional machine learning and deep learning approaches.
  • Analyze model compactness, reproducibility, detection performance, and suitability for forensic investigations.
  • Document findings and provide recommendations for future deployment of interpretable AI methods in automotive cybersecurity.

Krav

  • Motivated master’s student
  • Basic knowledge in computer science and cybersecurity
  • Specific skills in machine learning
  • Proficiency in programming languages such as Python
  • Proficiency in machine learning frameworks

Önskade kvalifikationer

  • Experience with tensor networks and quantum-inspired machine learning is a plus.

Förmåner

  • Collaboration with Swedish industrial and academic partners
  • Opportunity to work on cutting-edge security solutions
  • Flexibility to work partly remotely
  • Close collaboration with the Swedish automotive industry

Färdigheter

PythonMachine LearningDeep LearningCybersecurityTensor Networks
#Automotive Cybersecurity#CAN Bus#Intrusion Detection#Tensor Networks#Machine Learning#Forensics#Master's Thesis
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Om RISE Research Institutes of Sweden

As the challenges facing us as a society become increasingly complex, innovation alone is not enough; you need a strong innovation partner who can provide comprehensive support and a broad range of perspectives. This is where RISE comes in. RISE is a unique mobilisation of resources to increase the pace of innovation in our society. By gathering a number of research institutes and over a hundred test beds and demonstration environments under the umbrella of a single innovation partner, we create improved conditions for society’s problem solvers. We gather around challenges and organise…

Publicerade jobb

för 4 dagar sedan

Upphör

om 2 veckor

Anställningstyp

Praktik

Arbetsform

Hybrid

Erfarenhetsnivå

Junior

Platser

Kista, Sweden

Sundsvall, Sweden

Kvalifikation

Masterexamen

Sökande

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