Centre for Connected & Autonomous Automotive Research (CCAAR) PhD Projects

Dependability Assurance for Autonomous Vehicle Safety

Student: Luis-Pedro Cobos Yelavives

Project Summary:

The project aims to find a way to show how dependable vehicle assurance is. During the project a method has been developed that takes the aspects of Classical Safety (active & Passive), SOTIF (Safety of the intended function), Functional Safety, and Cybersecurity. The developed method uses the structure of GSN (Goal Structuring Notation) in combination with ADT (Attack Defence Trees) and challenges every claim, evidence and argument with inductive logic to reduce bias. So far there are 2 examples and a demonstration of the method

The traffic Signal Recognition System
AI driving
Pilot Demonstration.
Safety and Security Updates of a safety Critical Function like the Airbag
Test Bench of Updates
Ecu Analysis

Machine learning generation of attack trees

Student: Kacper Sowka

Project Summary:

The ultimate objective of this research is to produce a comprehensive machine learning supported attack tree generation methodology for the automotive cybersecurity domain. A principal aim is to explore how such a procedure could be utilised in practically viable cybersecurity assurance initiatives within the automotive industry, particularly in relation to the recently published ISO/SAE 21434 standard for automotive cybersecurity and UNECE Regulation 155. Of particular interest are methods for the encoding of salient cybersecurity critical information into individual vulnerabilities and the training of a machine learning model which can discern the relationship between two given vulnerabilities or weaknesses.

Design of generation methodology
Implementation of methodology with an automotive relevant example
Sourcing of dataset to train machine learning models
Comprehensive validation strategy determining the performance of the proposed methodology

Model Based Security Testing

Student: Esma Kalir

Project Summary:

The project seeks to augment the existing design methodology for automotive embedded systems with model-based security testing. This will increase the confidence that automotive systems are secure by design and that security properties are realised in the implementation.

Partners

The Centre for Connected & Autonomous Automotive Research (CCAAR) is a collaboration between HORIBA MIRA and Coventry University and is based on the MIRA Technology Park. Learn more about each company by clicking the Links below.